Conference Agenda (All times are shown in Greenwich Mean Time (GMT) unless otherwise noted)

Information horizons is a theory and method that embraces behavioral, cognitive and social aspects of information seeking, sharing, and use. As the first method originating in information science that uses a graphical data collection technique (Hartel, 2016), it has served as the underpinning methodology for numerous investigations for over 20 years. The method is often applied in studies of diverse communities not traditionally included in research, such as lower socio-economic populations. Information horizons is also valuable in teaching master’s and doctoral students about information behavior and importance of theoretical constructs. For example, over 700 master’s students at the University of Toronto have completed exploratory, empirical studies using the method. A strength of the method is its extensibility; researchers have extended and adapted the method for use with different populations and to investigate different types of information behavior. This panel will explore the varied applications of the information horizon method, engage the audience in open discussion about the information horizons method for research and teaching, and explore how theoretical and methodological approaches can be more effectively shared across the information science and related communities.

While the potential and benefits of research-practice partnerships are well documented, there is limited discussion around approaches and challenges of establishing and sustaining public library-university partnerships in LIS research to bridge the gap between research and practice. This panel brings together five groups of panelists to highlight a diversity of public library-university partnerships within LIS and their approaches, models, practices, and implications toward consequential pedagogies and programming at public libraries. Through a collaborative panel discussion, this 90-minute panel will convene scholars and members of the ASIS&T community to improve concrete approaches and practices involved in public library-university partnerships to develop pedagogies and programming that are informed by the voices, needs, and interests across various communities.

This paper explores the relationship between cultural heritage and collective memory through the lens of information. We explicitly frame the heritage-memory-relationship as constituting a theoretical foundation for the field of Cultural Heritage Informatics. In framing heritage and memory as information phenomena, we leverage two information frameworks that appear most suitable to host, translate, and overlay heritage and memory theory: Context, relevance, and labor (Fremery and Buckland, 2022) and Information as thing (Buckland, 1991). Altogether, this preliminary exploration 1) establishes a terminological understanding of cultural heritage, collective memory, and information/informatics; 2) maps these concepts with recourse to the Context, relevance and labor framework (Fremery and Buckland, 2022); 3) articulates cultural heritage informatics as the intersection of heritage and memory focused on processes of selection, transfer, and integration of historic information in the service of identity maintenance; and 4) offers a cultural heritage information framework that highlights the unique potential of Cultural Heritage Informatics to guide future information research in cultural information studies.

The primary goal of this paper is to explore users' desires for digitized historical image collections, examining their desires based on different use purposes and information interaction activities. In addition, we investigate the image attributes that users wish to search from the collection. To accomplish this, we conducted 21 qualitative interviews with active users of a digitized historical photograph archive. Our findings suggest that users' desires relate to three contexts: tools, collection, and socio-organizational issues. Moreover, our results indicate that users require support for various information interaction activities, not just searching. We found that users' desires vary based on their specific use purposes, and that users prioritize conceptual access points that can already mostly be generated through automated annotation methods. Ultimately, this study contributes to a better understanding of users' real-life image needs and offers implications for improving access to digital image collections.

Digital, community-based knowledge infrastructures confront complex, systemic challenges to their sustainability over time. From digital community archives to computationally amenable corpora, databases, or data models created by and serving research communities, these sites of grassroots knowledge production tend to be maintained without long-term institutional commitments. Yet, they hold unique cultural evidence of enormous value. Prior work on the sustainability of digital humanities scholarship has surfaced numerous factors in project sustainability, including technical, organizational, and financial concerns. The roles of communities themselves in sustaining community-based knowledge infrastructures, however, are under-studied. This qualitative, multi-case study of digital humanities projects and digital community archives addresses community-centered approaches to understanding and implementing sustainability for digital knowledge infrastructures. This study finds that communities of various kinds—from public communities to networks of research practice—conceive of the sustainability of their digital projects as inextricably linked to the sustainability of communities themselves. We offer an exploration of factors in the mutual relationship of sustainability between communities and their knowledge infrastructures, including how they support the wellbeing of individuals and cohesion among communities, and how they promote activism and advocacy efforts within broader publics and disciplinary cultures.

The open data movement is hyped as a sweeping strategy to democratize science, promote diverse data reuse, facilitate reproducibility, accelerate innovation, and much more. However, it is rare that the potential perils of open data are studied and discussed at the same level as these promises. As we invest more into open data, we need to study the full spectrum of what open data facilitates in practice, which can then inform future policy and design decisions. This paper does this by describing the data practices of one contrarian community, anthropogenic climate change (ACC) skeptics, specifically how they process, analyze, preserve, and share data through an investigative digital ethnography. Skeptics often reuse data in ways similar to conventional data reusers, although to unorthodox ends, with differing levels of trust and expertise. ACC skeptics’ data practices call into question the assumption that open data is a universal good. These findings have implications for data repositories and how they might curate data and design their database with this type of reuse in mind.

This paper reports on a qualitative meta-analysis that aimed to identify, qualify, and conceptualise territorial barriers to interorganisational data sharing (IDS). The meta-analysis adopted a total of 69 semi-structured interview transcripts, gathered in two previously completed case studies in China. Case study 1 aimed to develop strategies to overcome barriers to interagency sharing of government data in the development of China’s smart government services. Case study 2 was carried out to investigate and resolve the lack of inter-hospital sharing of patient data in China’s healthcare referral services. By adopting a thematic analysis approach, the meta-analysis pointed to 21 territorial barriers to IDS, which emerged in three themes: psychological ownership, territorial behaviours, and interorganisational dynamism. Territorial barriers that hinder IDS have not been systematically investigated to date. This paper offers a theoretical basis for future studies and serves as a call for more research on territorial barriers in data sharing activities.

Research data sharing is embedded in policies, guidelines and requirements commonly promoted by research funding organizations that demand data to be “as open as possible, as closed as necessary” and FAIR. This paper discusses the challenges of balancing privacy protection with data sharing in a PhD project involving long-tail, small-sized qualitative human subjects’ data. Based on experiences and feedback from project participants, we argue that privacy protection is about respecting the participants and their self-image. This can be achieved through dialogue and involvement of the participants building on the principles of shared stewardship. Further, we suggest that de-identification and plain language consent materials are better at protecting privacy than anonymisation, which in a digital data environment is difficult to achieve and not necessarily a sensible approach for qualitative data, where the gold is in the details. The literature indicates that it matters to participants whether data are reused for research or other purposes, and that they trust the institutions. This supports our claim that research data services must find better solutions for restricted sharing when necessary.

This study develops a grounded theory of how social scientists use resources to facilitate qualitative data deposit and the impacts on making data FAIR and CARE. Drawing from 15 semi-structured interviews with U.S. academic social science faculty who deposited data to ICPSR, I take a resource-centric perspective to address the need for theorizing scientists’ use of resources to bridge the gap between underspecified, heterogeneous data practices and repository requirements. The two primary contributions of the study are: First, I identify three types of resources that social science faculty use to structure data deposit routines: 1) bottom-up, 2) top-down, and 3) borrowed resources. Second, I import a theory from crisis informatics, ‘routine infrastructuring’ to explain how social scientists deposit data to ICPSR. Results reveal that the resources social scientists use function as ostensive routines. I argue routine infrastructuring is not only a way to enact routines, but also one that creates routines. Findings also show that scientists’ use of resources developed ‘in-house’ has a mix of beneficial and negative impacts for making data FAIR and CARE. The study advances the small but growing body of literature that examines routine dynamics from a resource-centric perspective to explain successful data deposit to repositories.

Large investments of public funds to curate huge volumes of various physical samples acquired and stored over decades, and in some cases centuries, provide ample reasons to make these items as openly accessible, as easily discoverable, and as well-documented as possible to ensure this investment results in reuse. The purpose of this study is to understand the curation behaviors of managers of physical collections. Six focus groups were conducted with twenty participants from several physical sample communities. Participants responded to open-ended questions that relate to the entire data lifecycle for their research objects. Results indicated that physical collections would benefit from use of universal metadata and data storage standards to increase sharing across domains. Both of these factors contribute to access and use obstacles all these collections face in different ways. In the context of managers requiring more investments to encourage reuse of these invaluable items, this study hopes to provide preliminary domain-agnostic data to inform design of collections cyberinfrastructure, resources, and services using actual curation behaviors.

This panel aims to discuss and critique the position of Information Science (IS) in European countries. This will be achieved through panel presentations and through critical discussion of key questions amongst the participants in the session. The introduction to the panel will identify issues that emerge from studies of IS in European countries, and in particular points that emerged from two previous ASIS&T Annual Meeting Panel Sessions. Presentations on the current situation of IS in the United Kingdom, Portugal, and countries from the former Yugoslavia will be given and briefly compared. The focus will then move to session participants, whose views on the state of IS in their own country will be solicited in a structured manner. Hosted by the European Chapter,

While the focus of information science and technology research is in information, sometimes the lack of information, information gaps and non-information can make an equally great or even greater difference. The purpose of this panel is to nuance the understanding of the absence of information and addressing the gap in theorising, investigating and working with information gaps and ‘non-information’ across the information field. Panelists present research conceptualising, documenting, and describing information gaps and non-information and how they are dealt with in the information field specifically addressing: 1) how conceptualisations of information gaps and non-information influence how they emerge as describable entities; 2) what approaches to manage information gaps and non-information exist in information science and technology research; 3) what aspects of information gaps and non-information different approaches address, make visible and invisible; and 4) how novel insights from the current state-of-the-art research can be translated to practice, policies and actions. Prof. J. Tuomas Harviainen (Tampere University) has participated in developing the panel.

With the development of technologies in big data and AI, data has become more and more central to users for various tasks in different contexts. Yet the concept of data behavior, an emerging concept that captures the actions and interactions of individuals with data in various contexts and situations is not explicitly defined and framed. Data behavior focuses on the observable actions and reactions of users when they encounter, discover, seek, use, or create data for individual or collaborative tasks, while data practice encompasses the entire spectrum of how people work with data, from creating and managing to sharing and reusing data, as well as the intentional and strategic decisions and actions involved in these processes. This panel proposes a conversation and discussion about the concepts of data practice and data behavior by drawing on literature in data practice, data curation, and information behavior. This panel aims to discuss, compare, and bridge data-centric and user-centric approaches to conceptualizing data behavior. It will also present some examples of data behavior research in different domains and scenarios. The panel will highlight the challenges and opportunities of data behavior research for information science and practice.

This panel centers on presentations that address spiritual and/or religious experiences through an information lens. The panelists will initiate a timely conversation about the ways in which individuals and communities make sense of their information worlds post pandemic and in contexts of high uncertainty (e.g., climate anxiety, increased polarization, AI developments). In examining coping strategies of the spiritual and religious kinds, the panel brings together scholars in a range of information fields to address the conference’s themes, including theoretical re-conceptualizations of contexts such as everyday lived religion and spirituality at the intersection of health and well-being, socio-technical arrangements, and evolving and diverse information practices. The short presentations and interactive engagement bring together an international group of emerging and established scholars into conversation, and will coalesce into the formulation of a research agenda on this topic. Speakers’ interventions will revolve around three connected questions: 1) How can religious and spiritual experiences be theoretically contextualized within Information Science? 2) What research approaches are most suitable for exploring spirituality/religion in our digital networked world? and 3)

What ethical challenges do researchers encounter in undertaking this type of research (especially during a pandemic) and how can they be effectively addressed?

Polarization of views (known as ideological polarization) is one of the greatest societal challenges of our time, potentially sewing distrust and hate among individuals and communities and threatening to undermine the fabric of democracy. Divisive issues such as abortion and gun control are ever-present and can drive issue polarization, and even affective polarization—a disdain for ‘the other side,’ which can further divide society. Social media has been flagged as a breeding ground for polarized views, with private groups and personalized algorithms facilitating self-creation of echo chambers that may lead to polarization. While there is prior research on the technological influences on view strengthening, scant Human-centered research exists and most of it has focused on view change in general, rather than view strengthening specifically. To investigate peoples’ experiences of view strengthening on social media, we interviewed 10 people who recently strengthened their views on important topics. While some took steps to avoid creating echo chambers (e.g., by seeking out opposing views), others intentionally created them to allow their views to strengthen without interference. These findings have important implications for designing social media platforms that support careful and conscious view strengthening while mitigating against the risk of information manipulation.

The fear of crime is an emotional response individuals have toward crime or the anticipation related to being the victim of crime. The increasing exposure to crime information presents considerable risks to people’s psychological health and well-being. Nevertheless, the fear of crime in online discourses is under-researched despite abundant conversations about crime. This work presents a mixed-methods study to comprehend how people disclose the fear of crime and what linguistic content or cues are associated with the fear. We gathered conversations about crime in the Baltimore subreddit. The content analysis revealed a necessity to differentiate between "experienced" and "expressive" fear of crime. The regression modeling identified strong factors related to the fear of crime, such as negative sentiment, objective expression, and first-person pronouns. This work extends the conceptualization of the fear of crime in online discourses and suggests potential ways to detect the fear automatically.

The mutual causal interdependence between offensive language use and negative emotions has been largely underexplored in the public event. Using 784,179 posts about the Tangshan violence event collected from Sina Weibo, nine themes were recognized based on framing theory. The mutual causal relationship between offensive language and negative emotions under each theme was examined through Convergent Cross Mapping. Results suggested that the mutual causal relationships between offensive language and negative emotion intensity under various themes were different with bidirectional causality under moral judgement, emotional venting, and power conflict, unidirectional causality under the vulnerable framework and the trust framework, and no causality under other themes. More detailed examination revealed special bidirectional or unidirectional causality between offensive language and some fine-grained negative emotions under the vulnerable framework, the trust framework, and secondary opinion. This study provides insight into the interaction between offensive language and negative emotions and helps emergency managers make targeted strategies to solve the problems of offensive language use and negative emotions.

Twitter has emerged as an important forum for discussion among academic librarians. We took a mixed-methods approach to study the thematic content and sentiment of tweets authored by academic librarians in the United States, Canada, and the United Kingdom. We found differences in the semantic content and themes present in the data from each country that point to differences in how librarians in each country engage on Twitter. We also present a methodological intervention by using two different sentiment analysis methods, VADER, and Zero Shot Learning, to classify posts by academic librarians. While more work remains to be done, we cast new light on how members of professional communities use social media. Our qualitative analysis identified 11 thematic categories in academic librarians’ Twitter discussions, with a focus on professional topics. U.K. librarians exhibited a higher frequency of labor- and employment-related terms compared to their U.S. and Canadian counterparts. Using the state-of-the-art Zero Shot Learning (ZSL) approach for sentiment classification, we significantly outperformed an off-the-shelf classifier like Vader. Sentiment ratios for U.S. and Canadian tweets were similar, while the U.K. displayed nearly double the positive-to-negative tweet ratio.

Today there is increasing emphasis on knowledge exchange (KE), the movement of knowledge and expertise amongst diverse groups to enhance research uptake, use, and impact in healthcare, government, and community settings. Library and information science (LIS) professionals are central actors in KE though community engagement, scholarly communication, literacy, and cultural heritage initiatives, but (how) is this work formally documented and evaluated? Through interviews with 24 information professionals working in varied settings, we considered how KE activities fit into the current library assessment and evaluation landscape. Using thematic analysis, we identified challenges with placing this work within current assessment practices and evaluation frameworks and showing its value, as well as a desire for alternative, more dynamic assessment and evaluation methods. We discuss these findings with respect to previous research in LIS and KE more broadly to consider professional and organizational implications.

Patron-perpetrated sexual harassment (PPSH) is a form of gender-based violence and a pervasive problem in libraries. However, contending with PPSH requires the performance of emotional labour by library workers because of workplace cultures and professional values that prioritize patron and institutional comfort. To better understand library workers’ emotional labour as they respond to PPSH, we analyzed 512 survey responses where participants shared their experiences of, their responses to, and feelings about, PPSH. Three responsive strategies emerged: acceptance, indirect refusal, or direct refusal. Overwhelmingly, library workers reported negative emotions about the incidents. Despite these negative feelings, library workers consistently responded to PPSH by performing emotional labour that upheld “polite and professional” values. Our findings raise concerning questions for the field of library and information studies about the implicit and explicit expectations placed on library workers to perform emotional labour in response to PPSH, particularly within the context of a feminized profession and with the knowledge that PPSH harms library workers. Our goal is to support library workers to “find a way to say ‘no’” to gender-based violence in the workplace.

In modern society, though public libraries must be equal and neutral “places” to address social problems such as the crisis of democracy and social isolation, it is unclear how the roles and functions of “Library as Place” appear in modern library management policies or practices. This study aimed to clarify the characteristics of public library policies in Norway and Oslo and the practices of the Oslo public library from the perspective of the “Library as Place.” Using Kawamoto and Koizumi’s (2023) model, a qualitative content analysis and case analysis were conducted of the roles and functions of “Libraries as Place” in Oslo, Norway, identifying the access to materials and information that libraries have traditionally afforded alongside the implementation of distinctive functions such as Cultural activities, Cutting edge, Improving life skills, and Meeting place as concrete practices. These functions contribute to public libraries becoming places in the heart of the community whose services are accessible to all.

Public library makerspaces are said to facilitate user empowerment, but this empowerment has yet to be fully explored in terms of how or whether it is occurring, or for whom. Libraries need to assess any processes of empowerment to evaluate their support for their users’ needs and to assess the success of their makerspace services. This paper addresses these evaluation needs by describing a checklist developed from ethnographic research in makerspaces based on Ivan Illich’s theory of “convivial tools,” which forward power to their users to decide how, why, and when to use them. This checklist translates research into practice with a tool for practitioners and researchers. It can assist librarians as they explore the impacts of their services on their communities, and can advance research about makerspaces and power for the purposes of social justice. It also offers an example of how to translate research into evaluative practice.

Growing global concerns over food safety, food price inflation, and climate change demand urgent attention in scientific fields. Food information behavior and practice have been a vibrant and growing research area in library and information science, following the user-centered paradigm shift and everyday life information needs, seeking, and use research since the 1970s. Research has shown that people engage with informal and embodied information to guide food practices (e.g., shopping, cooking, eating, and sustainability transitions). Food and health research challenge research methods and approaches in everyday information behavior and inform everyday practices, technological services, policies, and actions. In this panel, following a brief introduction, each panelist will share their research approaches and/or findings about food, health, and information research. We aim to invite and foster an open discussion with audiences to explore research opportunities, challenges, and approaches to studying food in library and information science. Hosted by SIG-HLTH.

This panel presents information research cases translating impact into practice, policy, and action that make a difference in varied contexts of study. Initiatives of collective impact are applied and/or proposed, and the following models of research and research studies, exemplifying critical collective impact and making a difference IN research and WITH communities, are discussed in the following three panel presentations: 1. Towards a Critical Approach to Community-engaged Information Research and Shared Knowledge; 2. From Research to Strategic Planning to Collective Action: A Logic Model Using Theory of Change to Further Civic Engagement for Racial Justice in Public Libraries; 3. Building a Smart City Portal for a Sustainable Future Through a Collective Impact Approach. The presentations are followed by critical engagement with the audience in the session to interrogate making a difference, what contributes to effective community engagement and translatable results, that is, difference in making (process) and making a difference (impact). Panelists represent both practice-based and academic settings who report on their research, projects, and reflections on applying collective impact in making a difference.

In a 2012 ASIS&T panel titled “Humanistic Information Science,” Melanie Feinberg, Jens-Erik Mai, Jonathan Furner, and Joseph Tennis argued that information science as a field “could be richer” if it were to embrace “humanistic approaches to information science” (Feinberg, Furner, Mai, Tennis, 2012). Approximately a decade later, this panel returns to foundational questions about science, the humanities, and information as a field of study to consider the relationship between the digital humanities and information science. How are information science and the digital humanities different? How are they similar? How might work done in one field make a difference in the another? What might digital humanists and information scientists have to say about translation and the transposition of disciplinary knowledge to and from each respective field? How might the translation and transposition of disciplinary knowledge in the humanities and information science inform practice, policy, and action in both and beyond? This panel will provide a forum for attendees to debate answers with leading information scientists and digital humanists from around the world. Hosted by SIG-HFIS and SIG-AH.

Failure in research is an underexplored topic in the information science literature. Many instances of research failure go unreported due to the success-oriented nature of academic culture, and academic publishing in particular. In not discussing, or failing to enable the discussion and reporting of research failures, important learning opportunities are being missed by the information science community. The aim of this panel is to explore these missed opportunities and to consider the need for approaches to research design, research collaboration and relationships, community engagement, publishing, mentorship, and teaching that will make room for such discussions to take place. The panel will bring together prominent information researchers to discuss failure in research in a series of short themed provocations and moderated group discussion activities.

An explosion at the Port of Beirut resulted in over 200 fatalities and displaced many more. Hundreds recorded and thousands shared the event, sparking discourse communities across social media. We provide a mixed-methods analysis of 26 TikTok videos about the port explosion. Our study involved a semiotic analysis of the videos and a content analysis of the related 21,150 comments. The discourse surrounding the explosion extends a growing body of literature on the role of TikTok in disseminating crisis-related information. We use a collective sensemaking framework to investigate how TikTok contributes to the understanding of an event. Our results advance an existing classification of crisis discourse, capturing distinctions between crisis discourse on Twitter and our study. In particular, we find that Middle Eastern content creators contributed more to collective sensemaking about the event than non-Middle Eastern creators. We additionally examine the current state of collective sensemaking on TikTok and provide platform implications.

The concept of ‘information crisis’ is playing an increasingly prominent role within information studies literature and practice. Yet, the term is rarely defined and its meaning often remains both inconsistent and ambiguous. This opacity calls for a greater grounding of the term if it is to become a key concept in the field, including how it operates and what it enforces. This short paper draws upon information studies literature to present a conceptual analysis of the information crisis concept. From this analysis, we argue that an information crisis framing is typically used to either establish the status quo, through centring challenges to established information ecosystems, or maintain the status quo, by outlining the operations needed to renew or protect these landscapes. These findings illustrate how ‘information crisis’ can obscure the very contexts of inequality and injustice through which crisis operates and delimits the possibility of changing/disrupting the status quo.

The aim of this paper is to examine the second- and third-level digital divides in U.S. society through empirical research on 5,253,530 web trajectory data of 642 unique participants. Through systematic analyses of the association between self-reported socioeconomic characteristics and the usage log, the paper exposed the inequality in application usage as a consequence of unequal cultural, temporal and capital resources. The research is strictly data-driven with a theoretical basis on the domestication theory and digital divide literature. This research can advise researchers and policymakers in understanding the multidimensionality of the digital divide and social inequality after the arose of tech giants and platforms.

Hacking is an opening gate to cybercrimes. Millions of hacked accounts are traded underground and misused for fraudulent activities. A majority of previous studies on hacking have been about hacked accounts detection and account security; however, relatively little is known about experiences of being hacked from gender perspectives. This study aims to explore experiences of being hacked with a focus on gender disparities from the perspective of the third-level digital divide—socially constructed gaps of digital use outcomes even among users who have similar digital access and skills. Tweets mentioning accounts hacked were obtained (N=13,731) and analyzed using topic modeling. Gender classification was performed on user profiles. Results show that women reported more experiences of being hacked in all online service types except gaming. Women were more likely to experience negative impacts of being hacked including reputational harm, money loss, and having personalized content modified. Furthermore, gender differences were found in coping strategies. Men were more likely to perform active strategies like warning others, rebuilding accounts, and deducing hackers’ origins. Meanwhile, women were more likely to seek help from others. The findings of this study imply that interventions to tackle cybercrimes need to be developed considering gender differences.

Data Science is a burgeoning area in the iField. But Data Science practices have far outstripped the field’s ethical safeguards. We argue that Data Science graduate education programs must address this critical problem. In this theoretical and conceptual paper supported by documentary evidence, we develop an ordinary macroethics that we call data flourishing. We contend that this macroethics is most appropriately developed through a holistic, human-centered data science (HCDS)-based pedagogy that concentrates on cultivating communities of ethical practice (COEPs) through social learning. We favor embedding this principle throughout iField programs’ graduate data science curricula and by extension, throughout the entire data science education enterprise. This paper aligns with the 2023 ASIS&T annual meeting theme of translating research into practice, especially the twin themes of “improving decision-making” and “understanding the power of information to develop human happiness, equality, and wellbeing.”

The Z-Inspection® Process is a form of applied research for the ethical assessment of AI systems. It is quickly establishing itself as a robust method to ethically assess AI in Europe. The process is predicated on the European Union's Ethics Guidelines for Trustworthy AI, outlining ethical principles intended to guide European AI development. In contrast, the United States has only recently released its holistic version of such guidelines, the Blueprint for an AI Bill of Rights. The aim of this paper is to assess the suitability of the Blueprint for an AI Bill of Rights as an ethical framework underpinning the use of the Z-Inspection® Process in the United States. This paper provides preliminary findings of comparative analysis of European and United States ethical frameworks for responsible AI development. Findings outline primary ethical concepts that are shared between respective frameworks. Findings suggest the US Blueprint is suitable as an ethical framework for the Z-Inspection® Process. There are notable omissions within the US framework which would require further development for Z-Inspection® use. Discussion will consider opportunities for adapting Z-Inspection® to the United States context, including contributions from the information professions and research.

This paper presents the history, internal processes, and finalized report of the Trans Metadata Collective (TMDC), founded to address the lack of attention paid to trans and gender diverse issues in galleries, archives, libraries, museums, and special collections (GLAMS). The TMDC, an ad-hoc group of nearly a hundred information professionals, developed best practices for the description and classification of trans and gender diverse information resources. These guidelines prioritize transparency, cultural sensitivity, correct identification, explicit descriptions of transphobia, and regular assessment of trans-related content. It examines the effects of commonly used standards and controlled vocabularies such as Resource Description and Access (RDA) and Library of Congress Subject Headings (LCSH) on trans and gender diverse people and critiques the inadequacy of these standards’ representation of those communities. The TMDC provides guidance for using existing LCSHs, recommends alternative subject vocabularies, and proposes revisions to improve representation. The paper advocates individual agency in naming and gender identification, with recommendations on contacting creators and documenting their preferences. The TMDC emphasizes the importance of minimizing potential harm and protecting privacy in metadata creation. Overall, the report aims to enhance the representation and inclusion of trans and gender diverse communities in GLAMS institutions.

Extant discourses in Indigenous Knowledge Management [IKM] emphasize the need to support Indigenous self-determination, data sovereignty and self-governance. To channel archival attention in this manner contributes to a larger shift in IKM towards stewardship praxes that empower Indigenous communities through culturally responsive and responsible praxes. The role of radical empathy in motivating this change, however, remains under-explored. In this paper, we introduce eight mutually inclusive empathy-driven propositions to transform the stewardship of Indigenous knowledges through an ethics of care framework. Grounded in a te ao Māori worldview in Aotearoa (New Zealand), we discuss how orienting ourselves to empathy motivates specific kinds of dialogic engagement that gives voice to Indigenous peoples in diverse global Indigenous contexts to share what cultural values should shape their research and knowledge stewardship. In doing so, we offer actionable ways to make positive differences in the lived experiences of Indigenous individuals and communities as they interact with and lead contemporaneous stewardship praxes.

The LIS Forward initiative is addressing the urgent question: As LIS evolves within the context of iSchools, how do we best position our research and education programs to lead the field and the future of libraries? The initiative stems from the recognition that the evolution of iSchools presents opportunities and challenges for LIS and that there is great value in iSchools working together on charting directions forward. The growing coalition of iSchools is working to support LIS in taking full advantage of the multidisciplinary knowledge and expertise within iSchools, foster future leaders who will champion LIS within iSchools, and confront the dynamic tensions in research intensive iSchools. This session aims to engage international, professional, and academic stakeholders to guide activities and coalition building that can continue to strengthen LIS in iSchools. A panel will present highlights from a recent position paper to catalyze interactive, facilitated dialogue within the ASIS&T community on critical issues in LIS research and education. Breakout sessions will generate responses and recommendations to advance collaborative planning and strategy of value to LIS academic programs and the profession.

This panel will present examples of how to conduct critical social justice research in Information Science (IS) that acknowledges intersectionality. Each of the panelists has extensive experience in designing and conducting IS investigations with communities underrepresented in research who may belong to various, interdependent social identities. The panelists will present their specific empirical research and/or make a theoretical contribution that applies the intersectionality framework. Each of the panelists will give a presentation followed by a Q&A session.

This panel considers the bridge between research and practice in cataloging ethics. Cataloging ethics – including indexing and classification – is an important part of practice, yet cataloging ethics research and practice are not always clearly connected. The purpose of this panel is to build towards more evidence-based cataloging ethics practice. Two main areas will be considered. The Cataloging Code of Ethics (2021) is a vital part of these discussions: this major codification of cataloging ethics was the result of both practitioner input and much research. This panel will discuss ways in which the Code can lead to more research-informed practices. Teaching and training is a crucial – and under-discussed – aspect of cataloging ethics, both within library and information science education and workplace training. Therefore, the panel will contemplate how training and teaching can germinate research-based practices. The panel will be in three parts: a panel presentation about cataloging ethics, including each member’s perspectives and experiences on teaching and training in cataloging ethics; small group discussions about real world cataloging ethics scenarios, utilizing the Code to generate discussion; and feedback to the whole group with a closing discussion about strengthening the relationship between practice and research in cataloging ethics.

Information Sciences is deeply invested in improving the future of AI across the globe. Information science researchers are providing a critical voice in the growth of AI by bringing in perspectives related to AI Ethics, diversity, equity, and inclusion, and AI education for all. AI is seeping into everyday life and is often a source of concern for people whose lives are impacted. The concerns of losing employment, inequitable access, and biases create a fear of AI among people. Library and information science educators and researchers have a rich history of working with local communities and representing local contexts. This experience places us in an important position to understand and evaluate AI applications and their varied impact in different contexts; for example, the same library-related AI application would have different results in Europe versus Africa. However, AI and its applications in the global context are yet to be discussed and understood in the information science community.

Academics argue that the COVID-19 pandemic has limited students' ability to learn, with significant digital inequities occurring between students from the global North and the global South. Students and academics from developing nations encountered particular challenges and difficulties with the move toward online styles of learning. Much like their colleagues from developed countries, they were unprepared for this predicament, but on top of the crisis context, deeper issues were having to do with digital inequalities and disparities that were exacerbated by the inadequate digital infrastructure (smart devices/gadgets, internet access, and speed) and online interaction abilities and practices. The goal of this panel is to address the pressing issue of digital inclusion in online education, specifically the broader challenge of ensuring that online education is accessible to all.

Challenges to books in libraries have sharply escalated from 2021—present. While currently concentrated in the U.S, book bans are becoming widespread globally; these challenges often adapt strategies honed in the U.S., such as astroturfing. In this context, astroturfing refers to an illusion of grassroots organizing, in which national, elite-led organizations covertly coordinate local actions. Astroturfing is another manifestation of mis- and disinformation which ends up stoking fires of partisanship and discontent. In this panel, we will examine book bans, astroturfing, and solutions to these challenges, from several distinct yet interrelated perspectives.

Libraries offer an array of programs and services–in and out of the library–that are infused with important learning principles and concepts and can provide children and families, particularly from underserved groups, with valuable access to these principles and concepts. And yet libraries often are unsure how to reach these groups, where significant barriers can hinder community engagement and access. A research study, [removed for blind review], employed value-sensitive design to develop co-designed tools and a toolkit to help library staff interact with and learn from community groups and partners using a strengths-based and social justice approach. Two of the co-designed tools were then tested with MLIS students at two universities, whose feedback yielded several valuable findings. Students indicated that the tools helped them develop a deeper understanding of underserved groups and their values and gave the students the time and space to reflect on their understanding of the socio-cultural and value contexts of their communities and the values they hold. This study can help libraries more effectively design strengths-based learning experiences that are meaningful and relevant to underserved groups and their values, particularly for children and families who do not or cannot come into the library.

Beyond the easy and equal access to massive online contents, will digital reading bring more social welfare values for disadvantaged groups? Take left-behind children (LBC) in rural China as example, whose mental health issue has widely aroused public concern. Lacking of sufficient parental supervision and educational resources leads to insufficient development of psychological resilience and makes them vulnerable to mental health problems. As psychological resilience is a critical protective factor for maintaining mental health, in this paper, we wonder whether digital reading could perform as an alternative way with easy accessibility and numerous resources to supplement LBC’s resilience development. We conducted a field questionnaire study on LBC (N=217) and investigated the predictive effect of digital reading on psychological resilience. After controlling sociodemographic variables and common resilience protective factors, hierarchical regression results demonstrated that digital reading predicted an additional 4.3% of the variation in resilience above the control variables, indicating digital reading a positive promoter of LBC's psychological resilience. Moreover, by systematically exploring the fine-grained digital reading variables, we also found intrinsic motivation to read and recreational digital reading (e.g., reading comics and communicating online) to be the two most stronger predictors of psychological resilience.

While accessibility is a core part of diversity, equity, inclusion, accessibility, and social justice (DEIASJ) considerations, disability and accessibility are rarely centered in Library and Information Science (LIS) curricula. The lack of disability and accessibility coverage is problematic since information professionals must have the required knowledge and skills to effectively serve patrons with disabilities. This paper presents preliminary findings from a content analysis of 39 pre-filtered syllabi examining how disability and accessibility topics are covered in LIS courses. While nearly all of the syllabi analyzed contained a high level of detail, only 13 were ultimately determined to contain a “partial” depth of coverage of disability- and accessibility-related content and two a “detailed” level of coverage. Even fewer syllabi included a conceptualization of disability or accessibility beyond simply including the words alone. The paper offers suggestions for LIS instructors to better address disability and accessibility within their syllabi and course content.

The research reported in this paper is part of a larger project focusing on the iSchools’ identity and interactions in a globalized world. This paper presents the research management strategy for conducting a global research project among international research communities, and for investigating the current research focus of iSchools members based on the insights of global iSchools’ leaders. It found that information management was the dominant research area and that digital humanities, data science, and “informatics+ scenarios” are the key growth points. The most significant contribution of iSchools to society lies in social services. The research focuses on and benefits worldwide iSchools by outlining development strategies and strengthening the connection between research and society to increase social awareness, influence and reputation.

This case study describes the development of a management and leadership (M/L) iSchool course. To design a course that balanced traditional topics with current professional needs, we identified M/L topics currently covered in iSchools’ curricula, then assessed the importance of these topics for information professions through a survey of academic and professional communities. Survey participants selected topics in the areas of information economy, organizational management, and project management that they thought were most important for iSchool students to learn. They also suggested additional topics related to communication, diversity, equity and inclusion (DEI), financial literacy and strategic planning skills. Thirteen survey participants were interviewed by the researchers; they suggested further topics related to emotional intelligence and personal skills, such as time-management, risk-taking and confidence. This paper aims to support a culture of transparency in curricula design and, by sharing methods, findings, and lessons learned, ease the faculty tasks of course development.

Data science may be used to determine similarities between musical scores. Programs are written in C++ to capture note progressions from musical scores and to compare progressions from different songs to identify overlapping areas. These tools enable the study of musical borrowing across musical genres and may assist in copyright violation cases. Results indicate that within the Celtic music genre, borrowing occurs across greater than 10% of the songs.

The citation of scientific papers is considered a simple and direct indicator of papers’ impact. This paper predicts papers’ citations through team-related variables, team composition, and team structure. Team composition includes team size, male/female dominance, academia/industry collaboration, unique race number, and unique country number. Team structures are made up of team power level and team power hierarchy. Team members’ previous citation number, H-index, previous collaborators, career age, and previous paper numbers are a proxy of team power. We calculated the mean value and Gini coefficient to represent team power level (the collective team capability) and team power hierarchy (the vertical difference of power distribution within a team). Taking 1,675,035 CS teams in the DBLP dataset, we trained the XGBoost model to predict high/low citation. Our model has reached 0.71 in AUC and 70.45% in accuracy rate. Utilizing Explainable AI method SHAP to evaluate features’ relative importance in predicting team citation categories, we found that team structure plays a more critical role than team composition in predicting team citation. High team power level, flat team power structure, diverse race background, large team, collaboration with industry, and male-dominated teams can bring higher team citations.

As of spring 2023, the scholarly community has been eager to explore how AI-produced content should be integrated into both academic writing and scholarly publishing. This paper investigates the prevailing responses to the introduction of ChatGPT in November 2022 and the interest that has been afforded it by both the academy and the publishing industry. A review of the published literature on aspects of ChatGPT authorship was carried out, finding that government and the publishing industry have unequivocally asserted that large language models (LLMs) like ChatGPT do not posses the traits of a person and are not able to author texts as a result. Other approaches, including practice, have been less vehement. To assess the integration of instructions on referencing ChatGPT using APA, top Google hits in the .edu domain were collected and analyzed over a 6-week period from March 14 to April 18, 2023, a time during which official recommendations of the APA Style were finalized. Findings reveal that librarians were quick to provide guidance, but slow to update that guidance, contributing to the potential for misunderstanding the affordances of and best practices for work with LLMs.

This article proposes a multilabel poem topic classification algorithm utilizing large language models and auxiliary data to address the lack of diverse metadata in digital poetry libraries. The study examines the potential of context-dependent language models, specifically bidirectional encoder representations from transformers (BERT), for understanding poetic words and utilizing auxiliary data, such as author's notes, in supplementing poetry text. The experimental results demonstrate that the BERT-based model outperforms the traditional support vector machine-based model across all input types and datasets. We also show that incorporating notes as an additional input improves the performance of the poem-only model. Overall, the study suggests pretrained context-dependent language models and auxiliary data have potential to enhance the accessibility of various poems within collections. This research can eventually assist in promoting the discovery of underrepresented poems in digital libraries, even if they lack associated metadata, thus enhancing the understanding and appreciation of the literary form.

In this short paper, we employ a month-long autoethnography to investigate the utilization of ChatGPT through metaphor analysis. We conceptualize three metaphors—unreliable narrator, court jester, and sounding board—that possess the most explanatory capabilities in describing what ChatGPT is, when it can be used, and how it can be helpful. We posit that grounding the use of ChatGPT in metaphors could facilitate discussions and streamline the intricate mechanism of Large Language Models (LLMs). Our study indicates that by proffering playful metaphors as substitutes to apocalyptic and arcane ones, we can enhance the accessibility and comprehensibility of ChatGPT for non-experts and policymakers, thereby potentially contributing to more informed and productive dialogues about the role and potential of LLMs in everyday life.

Based on the privacy calculus theory, users’ decision-making on privacy disclosure was traditionally viewed as a trade-off between perceived values and privacy concerns. However, recent studies suggest that the impacts of users’ cognitive style and platform trust cannot be ignored in the context of social media platforms. From a configurational perspective, this study explores how these factors collectively affect users’ privacy disclosure. Data from 452 respondents on a Chinese social media platform were collected through an online survey. The results suggested that users’ decision-making on privacy disclosure in social media is a complex process involving different configurations. For field-dependent individuals, the trade-off between perceived values and privacy concerns is less important than the role of cognitive style. For field-independent individuals, beyond the trade-off between perceived values in different dimensions and privacy concerns, their decisions are also contingent on platform trust.

Although there is much discussion of the theory/practice gap in library and information science, there is little research about how librarians use formal theory in their practice. Using a card sort and interviews, we explore the extent to which public librarians encounter or use theoretical concepts and models from information behavior in their reference practice. Results from our pilot study show that our procedures, including plain language descriptions of theoretical concepts and models printed on cards, are effective for eliciting examples of theory in practice. Librarians are clear about which concepts are relevant to their practice and can easily provide examples of real-world application. Results of the study will suggest which theoretical concepts might be most important for instructors to teach to students in reference courses and which translate best from the research to the practice environment. In addition, the examples provided by librarians of how they use the concepts in their practice will be useful for instructors as they try to engage students in learning.

Recent research on personalized retrieval technology has been actively conducted to meet the needs of users for seeking adequate information. To refine the retrieval, researchers are considering user behavior patterns in a variety of ways. In this study, we use eye-tracking metadata to predict users’ levels of comprehension as textual evidence for IR processes. Furthermore, we incorporated eye-tracking metadata on the Automated Readability Index (ARI), a readability assessment tool of an English text. Our research is largely divided into two tasks: i) comprehension evaluation task (CET) and ii) comprehension-based retrieval task (CRT). In the CET task, for predicting the comprehension level, we applied various regression models. Among them, the Voting regressor demonstrated the highest performance with a Spearman’s 𝜌 of 0.68. In the CRT task, we incorporated the level of comprehension predicted in the CET task and ARI score into the ranking results. We derived a sentenceBERT to find the relevant text for a query and the Normalized Discounted Cumulative Gain (nDCG) for evaluating the CRT task. The nDCG score for Comprehension Level only and that with ARI together were 0.65 and 0.78, respectively. Thus, applying ARI resulted in a higher nDCG score compared to comprehension level only.

Information behavior research to date has mainly focused specific cases or representative surveys at the individual level, because each individual has unique contexts that shape their behavior. However, they have not fully benefited from aggregate-level analyses due to mainstream theories’ focus on a contextualized understanding of information. To address this gap, we adopt the theory of local information landscapes, that focuses on the material aspects of community dynamics, and analyze national-level aggregate data on book circulations in public libraries across South Korea. By examining the relationship between socioeconomic status and public library book circulation, we discuss the potential to develop scalable theories and relevant data-driven approaches in information behavior research.

This study aims to explore the factors related to young women's Internet use for reproductive health information, specifically focusing on female college students. The research model is based on the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB). A convenience sample of female college students who have recently used the Internet for reproductive health information will participate in an online survey. The survey will collect demographic information, background details on Internet use for reproductive health, and perceptions of reproductive health behaviors. Data analysis will examine correlations among the perceptions and their association with the intention to continue using the Internet for reproductive health information. The findings will contribute to understanding female college students' influential factors and information behaviors, informing the development of educational programs, intervention strategies, and online resources to improve reproductive health outcomes and empower young women.

Introduced by Microsoft in February 2023, Bing Chat is a feature of the Bing search engine that integrates an OpenAI large language model (LLM) customised for search (Mehdi, 2023a). This poster compares the outputs of Bing Chat and a standard existing search engine (DuckDuckGo) in response to identical keyword queries and corresponding natural language (NL) questions. Specifically, we examined: (1) the length of Bing Chat’s responses and DuckDuckGo’s first page of search results, by number of website links; and, (2) the length of Bing Chat’s textual summaries, by number of website links. We found that, on average, significantly fewer websites were linked to in Bing Chat’s responses compared to DuckDuckGo’s search results. Our findings have important implications for website operators, who may receive less traffic and ad revenue if LLM-enabled search engines are widely adopted in the future. Human-Computer Interaction (HCI) will inevitably face the need for more research on human information behaviours adaptations in response to the changing search paradigm.

The current study developed a data literacy instrument with 20 contextual questions and conducted a multi-mode survey with 232 pre-service secondary teachers in a university system. Three-way ANOVA was used to test whether pre-service teachers with different characteristics (i.e., field of study, library use, and Internet use) performed differently on data literacy. Pre-service teachers got a decent overall percentage score. They performed better in “identifying problems” and “analyzing data” than in “transforming data” and “collecting data.” While pre-service teachers in humanities and social sciences performed better in “identifying problems,” those in sciences performed better in “analyzing data.” Humanities pre-service teachers with high Internet use scored significantly lower; social science pre-service teachers with high Internet use and low library use scored significantly lower; science pre-service teachers with low library use scored higher. Implications for future data literacy education and instrument design are discussed based on the preliminary findings.

The ICT advancement and people’s increasing cultural needs have stimulated China’s online form of cultural activity organization. With highlights on such a new trend, this paper analyzes the impact of the newly-invented online activity organization form on the participation ratio of parent-child cultural activities, which are vital in China’s public cultural service system. Regression analysis indicates that the online activity organization form reduces the impact of limited available tickets and web browsing. It also relaxes the special time limit for public participation. Such an online form of activity organization deserves further attention considering its flexibility and convenience valued by the public.

Innovation Open Data Contest (IODC) is an effective way to take advantage of public efforts to realize the great potential value of open data in the field of digital humanities. Previous literature focusses more on the challenge open data contest rather than innovation open data contest. Given this, understanding the underlying factors motivating participants to actively engage in the contest is necessary. Based on the task affordance theory and self-determination theory (SDT), this study aims to identify and examine how task presentation affordances of IODC influence participants' motivations and thereby shape their level of effort. We employ partial least squares structural equation modeling (PLS-SEM) techniques to analyze the responses from 215 individuals who have previously participated in the IODC. The findings indicate that participants' level of effort in the IODC is contingent upon their perception of relatedness and competence. Moreover, hedonic affordance and connective affordance positively influence participants' perceptions of relatedness and competence. Our findings contribute to the extant literature by proposing a theoretical model to understand the participants’ motivation and have practical implications for IODC’s organizers.

Understanding and defining cybersecurity-related concepts for the general public can often prove challenging due to their inherent complexity; consequently, visual imaginary emerges as an effective device for articulating and elucidating these abstract ideas. In this study, we leveraged an adapted version of the existing iSquare approach to explore people’s understanding of cybersecurity. We collected 499 iSquares from a broad-spectrum backgrounds of participants attending a prominent international cybersecurity exhibition in Taiwan. Our preliminary findings revealed that metaphors of physical security and warfare were the most frequently employed in participants' conceptualizations of cybersecurity. Participants’ work roles were also observed to influence their respective attitudes and perspectives as expressed in their pictorial representations of cybersecurity.

While accessibility is a core value of the American Library Association (ALA) and represents an important factor in striving for diversity, equity, inclusion, accessibility, and social justice (DEIASJ), coverage of accessibility varies widely in programs intended to equip future LIS professionals to serve patrons with disabilities. This poster presents preliminary findings from a larger research project examining library and information science curricula at 77 North American colleges and universities. Through thematic analysis of course descriptions and syllabi, the researchers found that digital topics in accessibility are addressed more frequently than physical ones. Further, LIS curricula largely overlook the needs of disabled patrons when covering accessibility. These factors present challenges for future LIS professionals serving patrons with disabilities.

In Spring 2020, the murder of George Floyd catalyzed calls for racial justice across the United States, ushering in a series of organizational and institutional responses. One response from Yelp, a popular review-based platform, included its addition of a searchable Black-owned attribute, a tag intended to signal its solidarity with Black businesses and communities. Analyzing a repository of over 300,000 Yelp reviews from Black and non-Black-owned restaurants in Los Angeles, CA, USA and Detroit, MI, USA, we pose the following question: How did the addition of the Black-owned tag impact the online reputation of Los Angeles and Detroit Black-owned restaurants on Yelp? To examine this, we use restaurant review counts and average star ratings as proxy measures for online reputation and track these metrics over the year following the platform design intervention. We find that the addition of the Black-owned tag did not create positive, sustainable change for Los Angeles and Detroit Black-owned restaurants. In all, we call attention to the disparate impacts of platform design features on users and communities, especially for Yelp and digital platforms seeking to effect racial justice through novel platform design interventions.

This study delves into the realm of information behavior research, examining the attitudes and information-seeking patterns of Polish and Ukrainian parents regarding vaccination. Amidst rising vaccine skepticism globally, understanding how individuals acquire and evaluate information about vaccinations is crucial for effective public health communication. Through in-depth interviews and surveys, the study examines how parents acquire information about vaccinations, evaluate the credibility of this information, and identify cognitive authorities that enhance information credibility. Preliminary findings demonstrate distinct information-seeking strategies between pro-vaccination and skeptical parents. Parents in favor of vaccination tend to rely on a single source, typically their doctor, emphasizing the authority associated with their role. In contrast, skeptical parents consult various sources, prioritizing close personal relationships and shared experiences. In contrast, skeptical parents consult various sources, prioritizing close personal relationships and shared experiences. Moreover, opponents of vaccination exhibit a stronger affective dimension when assessing source credibility. The study also highlights the distinctive use of books and articles among vaccine opponents, despite their general mistrust of science. This study contributes to the field of information behavior research, offering insights into parental information-seeking dynamics, and their implications for public health policy and communication strategies.

This research seeks to identify critical factors that have an impact on government knowledge base adoption, which is based on the local government of Yi Chang, a typical third-tier city in China. Firstly, the knowledge base and its development in Chinese local governments are introduced. Secondly, to build the adoption model, factors from the UTAUT and TOE framework were integrated and trust to knowledge base and intention to knowledge reuse are introduced. Thirdly, a questionnaire is designed based on the model and distributed to civil servants from Yi Chang local government. Finally, the proposed model is validated, and the collected data is analyzed by PLS-SEM. The results show the factors (effort expectancy, social influence, competitive pressure, trust to knowledge base, intention to knowledge reuse) have a positive impact on the adoption of knowledge base in Chinese local governments.

This study introduces and examines the “Multi-dimensional Interaction-Attitude-Usage Model” (MIAU Model), drawing from cross-disciplinary theories. The MIAU Model proposes dimensions of interactive data retrieval, including resource, technology, context, and dual-process-based cognition, and explores their relationships with user attitude toward systems and usage intention. To test the MIAU Model, a structural equation modeling analysis was conducted on the questionnaire data. The results support the proposed model. The MIAU Model suggests that resources, technology, contexts, and individual characteristics directly impact data searchers’ dual-process-based cognition. System 1-based cognition has a direct influence on system 2-based cognition. Moreover, dual-process-based cognition and contexts directly affect attitude and usage intention. Additionally, resources, technology, contexts, and individual characteristics indirectly affect system 2-based cognition through system 1-based cognition, and similarly, these factors indirectly influence attitude and usage intention through dual-process-based cognition.

People with shared health conditions, including contested conditions like central sensitivity syndromes (CSSs), are utilizing TikTok to both seek and tell visual illness stories—and to co-create health information in creative, mimetic, and platform-specific ways. This poster presents results from a pilot qualitative content analysis study of 100 TikTok videos and comments by people personally experiencing #fibromyalgia, a pilot codesign session with a CSS TikTok community member, and late breaking results from a dissertation in progress. These studies are the first stages in the goal to understand and support these embodied, creative, and often-collective storytelling abilities, necessary within the CSS community experiencing invisibility, stigma, and difficult diagnoses. The visual poster format enables discussion, with examples of TikTok videos illustrating 7 identified themes, iconographic elements, and examples of reoccurring creative choices and collective storytelling features. Last, of broader interest in our field, this poster presents methodological challenges and sparks for discussion of best methods for TikTok research, including: (1) a novel sampling approach addressing gaps in current research and the slippery definition of TikTok communities, (2) a brief description of preliminary codesign findings and the method’s promise in this domain, and (3) discussion of critical disability studies perspectives guiding this research.

Drug-Drug Interaction (DDI) may affect the activity and efficacy of drugs, potentially leading to diminished therapeutic effect or even serious side effects. Therefore, automatic recognition of drug entities and relations involved in DDI is of great significance for pharmaceutical and medical care. In this paper, we propose a generative DDI triplets extraction framework based on Large Language Models (LLMs). We comprehensively apply various training methods, such as In-context learning, Instruction-tuning, and Task-tuning, to investigate the biomedical information extraction capabilities of GPT-3, OPT, and LLaMA. We also introduce Low-Rank Adaptation (LoRA) technology to significantly reduce trainable parameters. The proposed method achieves satisfactory results in DDI triplet extraction, and demonstrates strong generalization ability on similar corpus.

There is increasing recognition of the challenges academics working on short-term contracts experience, as well as universities’ increasing reliance on their labor. While discussions of these issues have expanded, there is a lack of empirical research around the information experiences of contract academic staff. This poster reports on initial findings of a qualitative research project that interviewed 34 contract academic staff (CAS) from across Canada, exploring institutional provisions of information, information practices in the workplace, and how marginalization and social inclusion influence workplace information practices. We present preliminary findings in three themes: precarity and uncertainty necessitate holistic and situational understandings, exclusion and isolation are enacted and experienced on many levels, and uncertainty as a barrier to investment and furthering careers, exploring what these findings mean for contract academic staff members.

This study represents our preliminary work focused on the health information seeking of caregivers of ovarian cancer (OvCa) patients and survivors. Previous research has predominantly focused on OvCa patients' needs, while neglecting caregivers' needs independently. Through the analysis of social media posts by OvCa caregivers, this study explores seven categories of information needs desired by caregivers and examines how these needs evolve throughout the disease trajectory. By distinguishing between caregiver-specific needs and those on behalf of the patient, our study contributes to the development of a holistic caregiver support framework.

This study uses the UK as an example to explore the structure, content and governance network of scientific data ethics policies. Adopting grounded theory (GT) and Social Network Analysis (SNA), Nvivo12 is used to analyze and summarize the structure and content of scientific data ethics policy, and Ucinet and Netdraw are used to map governance network reflected in policy. Results indicate that the structure covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. Governance network indicates that research institution plays a central role in ethics governance and the core of the governance content are ethics governance initiatives and governance guidance.

New media platforms have enhanced the efficiency and diversity of information dissemination, providing new possibilities for the dissemination and promotion of academic papers. Currently, a large number of Chinese academic journals from different disciplines have established WeChat official accounts to promote their papers. This study examines WeChat official accounts from three disciplines: social sciences, natural sciences, and medicine. We analyze the existing paper promotion methods employed by these academic journal official accounts from four dimensions: content presentation format, number of papers promoted in a single post, interactive forms, and publishing time. The findings reveal that the current promotion methods for academic papers on WeChat official accounts are relatively limited, with low utilization of multimedia content. Therefore, there is a need for further improvement in new media promotion for academic papers.

The trend of multilingualism in the web environment has put new demands on the digitization of cultural heritage. However, minority languages in cultural heritage have received little attention in China. This study selects traditional Tibetan festivals, a representative minority cultural heritage in China. Based on constructing a Chinese-Tibetan bilingual ontology, the cultural and tourism data of Tibet are linked. By further constructing a knowledge graph, a Chinese-Tibetan Bilingual Tibetan cultural service platform with traditional Tibetan festivals as the core is established.

Data sharing has been an extensively discussed subject in both the information science and biomedicine communities. However, the two communities do not seem to speak to each other. Such an absence of exchange of perspectives can lead to siloed knowledge, duplicated work, and hindered collaboration. To uncover existing knowledge gaps, this poster depicts the bibliometric relationships between relevant literature in the fields of information science and library science (ISLS) and biomedicine and health sciences (BMHS). The findings demonstrate stronger bibliographic couplings within ISLS publications and between ISLS and multidisciplinary science publications, compared to the BMHS group. In addition, the examined ISLS and BMHS publications exhibit distinct topical foci on open science. This poster is expected to serve as a first step toward stimulating more conversations in the information science community, as well as bringing the discussions to the biomedicine community in the near future.

In January 2023, heavy California flooding prompted users to capture and share video footage of their impacted surroundings. This preliminary study uses this crisis event to compare commenting behavior across three video content formats: YouTube videos, YouTube shorts, and TikTok videos. Using network and regression analysis to study 45 videos across these three formats, we find that users commented and replied to others more on YouTube than TikTok despite TikTok videos having more views than YouTube videos. Additionally, we find the most vibrant comment behavior under YouTube shorts. This work provokes additional research to understand the exact ways in which platform design and affordances can influence crisis communication around a specific event.

The application of AI(artificial intelligence) in libraries is not only the result of the development of technology, but also the choice of libraries to improve their service. However, how to better integrate libraries and AI still needs further exploration, and libraries also need guidance in implementing AI technology. This study uses a systematic literature review method to analyze the literature on the application of AI in libraries published before 2023. Based on sorting out the application of AI in libraries, this paper summarizes and analyzes the practice and attitudes of applying AI in libraries. We find that there is a broad prospect of AI applications in libraries, but the current application is scattered and lacks a comprehensive view. There are different attitudes towards the application of AI in libraries and it is important to learn about different views.

The poster discusses varying data collection approaches in investigation of an organization’s data governance practice of a single case study. The aim is to promote transparency in data governance practice on a case-by-case basis and to unveil the circumstances of adapting approaches in data collecting. Four distinct data collecting approaches were utilized in this study, each tailored to diverse needs and scenarios, including group interview, design-thinking workshop, semi-structured interview and field study. Clarifying the rationale of taking certain approaches, the research team aims for providing the benchmark for future data governance research.

This study investigates the practice of data-driven decision-making in higher education institutions in Ethiopia. It presents the results of a mixed-methods investigation that was conducted at two public universities in Ethiopia. Data was collected via a survey questionnaire from 91 faculty members, nine ICT experts, four higher education registrar experts, and 194 graduating undergraduate students. The study also involved interviews with two directors from the university's education program relevance and enhancement office and four senior officers from library departments. The findings revealed that the majority of the instructors used manual data analysis and basic software like MS Excel. Institutions use many disconnected in-house systems for different activities without intelligent tools or data warehouses to support data analytics. The results indicate deficiency in activities that promote data analytics and data-driven decision-making, such as capacity-building training and leadership support within institutions.

Drawing on the need to shift from competency-based information literacy instruction to critical information literacy instruction, this study examines scholarly communication and scholarly misconduct in the health sciences based on literary evidence. We report on a qualitative systematic review of forms of scholarly misconduct in the health sciences and participants' attitudes towards these phenomena, with the goal of developing new, critical, approaches to information literacy instruction. The data synthesis process indicates there are four major areas of misconduct in health science research: in conducting research, publishing, following research protocols and determining authority. This categorization informs a framework for critical information literacy dispositions and pedagogies for researchers across health disciplines and geographies.

The availability of large scholarly full-text datasets with in-text citations annotated opens the opportunity to investigate how articles have been cited in scientific literature at scale. However, duplicate documents may exist in a dataset, and these duplicates may impact downstream analysis such as calculating citation counts. Document conflation is the task of identifying documents that are nearly identical to each other. This study evaluates document conflation in the Semantic Scholar Open Research Corpus (S2ORC), a dataset containing over 12 million scholarly articles. The evaluation was based on 6,099,232 full-text S2ORC documents with PubMed IDs (PMIDs) or PubMed Central IDs (PMCIDs). Our findings showed that a portion of S2ORC might contain duplicates. Of the 6,099,232 full-text documents, 1,280,196 (20.99%) had the same PMIDs or PMCIDs as at least one other document. Pairwise comparisons of their full text found that at least 9.44% of the documents in S2ORC had duplicates.

This is the first on-going project presenting a four-dimension metric to identify scholars’ emotional intelligence (EI), which has yet to receive much attention. Current study proposes a data-driven metric rather than a subjective survey to reflect EI’s first dimension, self-awareness. By employing paired-T-tests on the DBLP dataset, we found that highly self-aware scholars are more likely to strive to improve with higher stability, leading to higher productivity and impact. Meanwhile, they have a more significant number of higher diverse collaborators. This research highlights the importance of one’s self-awareness to his/her scientific performance.

This poster problematizes selected presentations and outcomes of an IFLA satellite conference on the history of professional organizations of librarians and information scientists. Representatives from organizations, including ASIST and library associations around the world from four continents (Europe, North America, Asia, Africa) will meet at the Mundaneum in Mons, Belgium. The theme of the conference is “Preserving our origins: Approaches to the organization, curation, and historiography of the record of national and international organizations in libraries, information, and documentation.”

An irony within information science is that its many professional associations often fail to identify and preserve their own history. Their work is documented, but often not well preserved, and hidden from a wider audience. Born digital materials are especially vulnerable to loss (Neal, 2015). This poster identifies problems and best practices in managing the documents of historical value of volunteer-led associations and invites ASIST members to contribute to the historical work of the association.

The goal is to identify common problems in preserving association histories. The poster will present several projects discussed at the IFLA satellite conference, as well as proposed ways forward that will advance historical work for the information professions.

This research analyzes the results of a study that is part of a larger, interdisciplinary, and multi-institutional project that examines the usability and effectiveness of virtual reality (VR) training for library and information science (LIS) graduate students and professionals in gaining skills for interacting effectively with patrons in crisis. This paper reports on key findings related to the effectiveness of VR training for teaching empathy, confidence, and de-escalation skills for LIS graduate students. The findings illustrate that VR has the potential to impact LIS graduate education by reaching a wider audience that introduces training in low-stakes, immersive environments and that does not pose harm to patrons in crisis. This study also contributes innovative approaches that support training in skills including empathy, confidence, and de-escalation.

Until recently, research on information behavior and practices has focused on a series of actions, including having information needs, seeking information to satisfy those needs, and using the acquired information to varying degrees. However, in digital environments with an enormous distribution of information, it is necessary to consider information practices by focusing on their relationship with negative behaviors, such as information avoidance. Based on the discourses by Japanese Canadian seniors on information behavior during the COVID-19 pandemic, this study attempted to construct an expanded model of everyday information practices (EIP) that incorporates the concept of information avoidance into the EIP model proposed by Savolainen. Findings suggest that information avoidance is likely related to an individual's social context and that, as a result of information avoidance, different means of information acquisition are chosen from a person’s stock of knowledge, resulting in different aspects of the individual's information practices.

Much work has been carried out to highlight the accessibility challenges of blind programmers. Yet, relatively little has been known about how blind programmers help each other to solve problems. We present a data-driven approach to explore collaborative problem-solving of users in the Program-l community of, by, and for blind programmers. We collected 8,344 longitudinal email threads from 778 users from 2004 through 2022 to observe the dynamics of collaborative problem-solving among blind programmers. Our embedding-based topic modeling and assortativity network analysis reveal that the knowledge of blind programmers diverges between when asking and answering questions. Our findings also suggest that users who have a high cluster level in the first year of activity and members are more likely to interact with other members with different roles. Our paper contributes to the field of social computing by introducing the first large-scale study of a unique community of blind programmers.

Today, while one sector can effortlessly gain access to data provided by another, there may also be instances of injustice between data producers and decision-makers. This study applies Heeks and Shekhar's framework of data justice to analyze two humanities and citizen science projects in Taiwan: the collection of old photos by the Taipei Public Library and the citizen archivist project of the National Archives Administration. The study explores data justice issues within libraries and archives and examines the applicability of the data justice framework to citizen humanities projects. The research findings indicate that although there are unequal power dynamics between institutions and citizen scientists regarding data, the selected cases involve relatively straightforward task contexts and individuals, resulting in minimal violation of data rights for citizen scientists. Consequently, these two projects have limited observable instances of data injustice.

This poster reports on the preliminary findings of a phenomenological investigation of humanities researchers’ perceptions of “data” to develop workable strategies for future collection and curation of research materials used for humanities research. An archival approach is proposed to curate individual humanities researchers’ research materials.

As advancements in artificial intelligence (AI) technology have opened new avenues for artistic expression and creation, human-AI collaboration in creative activities has garnered increasing attention. Through semi-structured interviews with 15 participants, we investigate the intrinsic and extrinsic factors that motivate laypeople’s engagement with AI painting, as well as challenges and concerns faced by users. Our findings reveal that laypeople engage with AI painting for emotional needs like entertainment, aesthetics, surprise, and curiosity, personal utilitarian needs such as self-expression and customization, and social interaction through sharing and communication. Despite the appeal of novelty and unpredictability they also encountered challenges related to technical and system functionality, personal and environmental factors, as well as concerns about algorithm bias, pornography misuse, employment risks, copyright disputes and ethical implications. Findings provide preliminary evidence of the potential and limitations of AI in democratizing creative activities, and offer implications for designing and developing of AI assistance tools.

This poster describes the research design to study the information behaviours of individuals with diverse sexual orientation and gender identities (SOGI) and how they negotiate between their personal privacy and their social and public identities in the digital world. In Australia, there is no legal right to privacy, and our increasing reliance on new technologies has created legal and regulatory challenges, especially for vulnerable populations such as persons with diverse SOGI. The poster will outline the literature review, research questions, aims, and methods guiding the research. Methods proposed for this study include an analysis of legal frameworks and policies, a survey of approximately 100 people with diverse SOGI about their use of digital social technologies, and in-depth interviews with a sub-set of self-selected survey participants. Information behaviour theories and privacy literacy theories will be used to understand participants' behaviours and experiences regarding how they use digital social media, and the practices they have in place to manage their privacy.

A paradigm shift is currently underway with the emergence of the Collections as Data movement, which advocates the creation and dissemination of cultural heritage collections that are amenable to large-scale computation to empower both collection managers and users. Although this discourse is beginning to gain some traction in the literature, critical evidence-based assessments of the opportunities and risks of this process are underexplored. This paper presents the results of a content analysis of the official position statements (n=83) produced in the Collections as Data forums and written by international professionals working with digital collections. Although preliminary, the analysis presented and discussed here sheds light on the initial reception of the idea of Collections as Data and its articulation in practice. The study represents the first systematic attempt to explore the complexities of the intersection between ethics and artificial intelligence in the context of cultural heritage, aiming at providing a valuable precedent for further elaboration and discussion.

This study investigated how digital human can help libraries promote reading. This study recruited 103 participants for a user experiment to explore their satisfaction with reading promotional videos using digital humans. At the same time, the effect of using digital human in library reading promotion was analyzed from the perspective of whether users are willing to share and interact. Research has found that user satisfaction with them is not high due to digital human presence in their voice and intonation. But users are more interested in using anime digital human videos. This discovery can help libraries better carry out reading promotion and digital services.

This study aims to investigate the topics regarding disabled people in library and information science research areas through systematic content analysis, with the intention to profile the critical issue of accessibility and its development in LIS research and practices. 330 research papers in LISA published during 2011-2021 were collected and analyzed to understand the distribution of the research topics, subjects, methodologies, and findings about disabled people. The results showed an extended period of user-oriented research concerns yet very little exploration of service framework issues of policies, legislation, and technical services, in actual practices. Based on the results, specific and necessary research topics and issues were identified for future studies.

This study explores the impact of the COVID-19 pandemic on informal online learning behavior through the lens of online video tutorials hosted on YouTube. Over 40,000 YouTube comments were collected for topic modeling analysis and uncovered thirteen latent topics related to three learning behavior types, that is, environment structuring, help-seeking, and self-evaluation. These learning behaviors underwent varying degrees of change after the pandemic declaration and normalized after that, highlighting the importance of adapting teaching methods to meet the changing needs of learners in response to any learning disruptions.

This study uses an exploratory, sequential mixed method design to explore how Kuwaiti students share academic information using social media. Phase I involved in-depth, semi-structured interviews with 12 undergraduates; in Phase II, 683 students completed online questionnaires.

Extensive use of social media, especially WhatsApp groups, was discovered, and the main patterns were providing information, exchanging information, and non-sharing. Before sharing, students evaluated information accuracy, provided instructions, and reviewed information with others.

Motivations for sharing were enjoyment in helping others, mutual interest, enhancing one’s reputation, and reciprocity; reasons for non-sharing included self-doubt, fear of information being used for cheating, and competition. Class news, summaries, class notes and materials were shared for group projects, written assignments, presentations, and exams. Online leering used during COVID-19 accelerated sharing behaviors, and older students shared more actively and in more diverse patterns.

A new conceptual model was drawn to explain these complex behaviors, and recommendations were provided for supporting them.

Most workers’ activities in the workplace can be classed as knowledge work (KW). Previous research has described workers’ tasks very broadly, making it difficult to know the actual work undertaken. We hypothesise that deconstructing what goes on inside a task could reveal many subtasks and activities at levels that are, as yet, unexamined and in need of deeper understanding. To explore this further, a data set collected from research fellows who described a specific knowledge work task was examined. The task was broken down into many subtasks and activities, showing that one single task contains many levels of tasks. This level of understanding may allow for the development of tools to support the worker.

It is a common phenomenon for Tang poems to cite the allusions, which can generate a rich relationship network. However, insufficient attention has been paid to investigating the relationship network. To address the research gap, by employing the theories and methods of information science, this study presents a method of combining fine grained co-citation relationship and semantic features to link allusion words. We constructed a fine-grained co-citation network between the allusion words by adding the cited positions and sentiments. We then transformed the fine-grained weights into relational similarities. Moreover, we also leveraged the explanatory texts as semantic information of each allusion word to map the semantic embedding vectors and calculated the similarities as the semantic similarities. Finally, we applied the link prediction algorithm to implement the allusion word linking. Our experimental results reveal that adding the cited positions and sentiments as well as semantic similarities can improve the performance in the task of allusion word linking and achieve 0.869 on AUC score. Additionally, we explore the linking results from the perspective of the shortest path and find some regular knowledge. Overall, our study extends the application scope of information science and promotes the development of Chinese traditional cultural resources.

This poster captures the initiatives of African community and public libraries in the early stages of COVID-19. This is part of an ongoing research on the impact of the COVID-19 and long-term implications for African libraries. We conducted 11 interviews in 9 countries using both purposive and snowball sampling. We analyzed the recorded data through a thematic analysis approach. Arising from the data, we found that librarians employed empathetic information interventions using widely available information technology tools to deliver critical information to promote the well-being of their communities. The libraries initiated social cohesion talks to foster unity among families. They also used WhatsApp to send snapshots of study materials to examination candidates and to point people to social services. This work contributes data to scant literature about the initiatives of African community and public libraries during the COVID-19 and how low resource libraries can support their communities in crisis.

In academic Q&A, question cues are characteristics of natural language for responders to understand askers’ needs. However, knowledge is limited concerning responders’ answerability evaluations which could be influenced by question cues (e.g., emotional expressiveness, complexity) and topic types. To address the gap, this research conducted an experiment to investigate how different question cues and topic types influence evaluations of question answerability. Sentiment analyses were conducted to assess responders’ evaluations of question answerability. Results showed that responders favored answering complex questions rather than simple ones. Responders also held more divergent opinions regarding whether to answer STEM questions with different cues while holding a more inclusive answerability evaluation of non-STEM questions.

This study collects heterogeneous information from multiple sources related to the Grand Canal, a cultural route in China, to construct a multilingual ontology of the Grand Canal. The research designs a data translation, optimization, and multilingual ontology construction method to reveal the internal and external characteristics and associations of the Grand Canal, which can provide users with multilingual and ordered knowledge of the cultural route, providing a feasible solution for digital preservation and global sharing of the cultural routes. On this basis, a multilingual knowledge intermediary platform is built.

The Nineteenth-Century Short Title Catalog (NSTC) attempts to provide comprehensive coverage of the print record in the English-speaking world from 1801 to 1918 based primarily on the catalog records of Britain’s five legal deposit libraries during the 19th century. Previous studies have used the NSTC to quantitatively study broad trends in Victorian-era British publishing, but they have not sufficiently acknowledged the NSTC’s limitations. This study works within the NSTC’s limitations by using it to quantitatively study the phenomena of legal deposit. Analysis of two, 90-volume random samples of first edition English novels reveals the impact of changing library acquisition practices and legal deposit legislation on the comprehensiveness of Britain’s legal deposit libraries, as well as the NSTC’s comprehensiveness and how it can be utilized for quantitative book history despite its deficiencies.

Existing models of the work of analytics teams and how they impact health organizations do not describe the activities, nor their relationship to the organization, in sufficient detail for optimal decision making. This poster reports on an ongoing study of the work of healthcare and population health analytics teams to rectify this gap. We are interviewing members of analytics teams in healthcare and population health organizations to gather data on the processes, deliverables, downstream and upstream stakeholders, and artifacts that the teams rely on to conduct and manage their work. The primary analysis uses a grounded theory approach, with a secondary activity theory analysis of relationships between the analytics team, identified cognitive artifacts, and intended outcomes. In this poster, we intend to present the methods, participants, and some preliminary observations. We hope that this presentation will solicit feedback that leads to improvements in the study.

This study determined that 18.6% of 199 recipients of Sloan Research Fellowships in Mathematics between 1955 to 1979 did not change institutions during the first 40 years of their academic careers after obtaining a doctor of philosophy degree. The results indicated no significant difference in the average productivity per researcher when they were categorized by their number of home institutions. However, average productivity differed significantly between recipients with and without international mobility. The results indicated an increasing trend in annual average productivity for all groups of researchers with international mobility except for researchers with one home institution. The inconsistent findings for the four main groups merit further investigation of the relationships between the number of home institutions, international mobility status, and productivity.

This poster presents public library innovations during the Covid-19 pandemic. Many public libraries quickly adapted to the pandemic environment, changing and improving their operations and services to meet the new challenges and demands from their users. We collected two datasets to investigate these innovations: the first dataset comprised 751 tweets from the 12 largest public libraries in the U.S., and the second dataset included 72 articles from 3 major professional magazines. These datasets were analyzed to identify innovative services provided between 2020 and 2021. A rigorous content analysis involving multiple coders was conducted. The findings from both datasets highlight that public libraries quickly changed their service delivery modes and implemented diverse innovative services to bridge the digital divide, support health and technology literacy, and help with unemployment and career development. Libraries made efforts to reach out to their communities during lockdowns and also served as community education centers during difficult times, combating with misinformation and focusing on assisting marginalized populations. Additionally, the magazine articles introduced innovative services that pertained not only to user services but also to internal operations within public libraries.

Examining the factors influencing the decision of Library and Information Science (LIS) professionals to leave their positions, we conducted a survival analysis using the WILIS2 dataset, with a specific focus on professionals of color. In our study, we investigated the impact of the comfort level with newer technology and the perceived effectiveness of online courses during their graduate program on professionals' retention decisions, while also examining potential differential effects across racial groups. The results revealed that both the comfort level with newer technology and the perceived effectiveness of online courses were significantly positively associated with professionals' decision to stay in their positions. Importantly, we found no significant differential effects of these factors across different racial groups. These findings provide empirical support for promoting a comfortable level of technological proficiency and recognizing the value of online education as effective strategies to improve retention rates among LIS professionals, particularly those from minoritized backgrounds. Additionally, we discussed the implications of our study for Equity, Diversity, Justice, and Inclusion (EDJI) in the field, and offered suggestions for fostering an inclusive and supportive environment based on our findings.

This study employs a scientometric approach to shed light on the evolving intellectual structure of AI in healthcare (AIH) research. The results substantiate the multi-layered nature of knowledge production within the AIH domain, comprising the foundation, technology, and application layers. The application layer has witnessed a notable expansion in both its scope and depth, encompassing diverse areas including medical image analysis, data analysis and mining, decision support systems, and intelligence assistance. Additionally, a significant shift has occurred in its knowledge production process, wherein the conventional reliance on empiricism has been augmented by the incorporation of datafied innovation. This process of datafication has enriched the empirical underpinnings of AIH research, fostering a more comprehensive and evidence-based approach to knowledge production.

We are a team of citizen science volunteers and academics presenting new information about how long-serving Old Weather project volunteers left the leading citizen science platform, Zooniverse.org, and created their own opensource transcription tool to capture meteorological data from historic ship logbooks, for climate science. The value of a hierarchical model of crowdsourcing, whereby an organization creates a project and invites volunteers to perform defined tasks, is well-established (Brabham, 2013; Estellés-Arolas and González-Ladrón-de-Guevara, 2012), as is the value of co-productive models between organizations and volunteers (Hedges and Dunn, 2018; Ridge et al, 2021). Information about how crowdsourcing projects evolve from hierarchical to co-productive models, and how volunteers create tools as part of such a transformation, is less well-known. We present how OW volunteers created a tool for high-quality data collection, and implications for citizen science collaborations.

The outbreak of COVID-19 has resulted in an increase in health misinformation spreading on social media, emphasizing the need for effective science communication to combat this issue. This study aimed to analyze the relationship between misinformation spreading and science communication network. We identified misinformation spreaders, scientists, and laypeople from COVID vaccine-related tweets, and we carried out network analysis to examine the ingroup and intergroup interactions. We found that individuals in all three groups tended to interact with people who were dissimilar to them. Additionally, we found that misinformation spreading, and science communication network are polarized. Finally, suggestions were provided to achieve higher engagement of science communication.

The Result Assessment Tool (RAT) is a software toolkit for conducting research using results from commercial search engines and other information retrieval (IR) systems. This software combines modules used for the design and management of studies, the automatic collection of search results through web scraping, and the assessment of search results by jurors using different scales in an assessment interface. Due to the flexibility of RAT, several types of studies can be implemented, for example, classification studies and qualitative content analyses in addition to classic retrieval tests. Therefore, RAT is a versatile tool and useful in various disciplines.

The following poster reports the preliminary results of a comparison between a 2017 survey on health information and the same survey administered in 2023. The primary research question is: How did the COVID-19 pandemic impact undergraduate students’ judgement of credibility in health information sources? Recent research has shown that student health information seeking has changed around the COVID-19 pandemic. However, the research has not noted whether the pandemic has had a lasting impact on credibility of sources during health information seeking at the presumptive tail end of the pandemic in 2023. The original study in 2017 surveyed the undergraduate population of McGill University. The same survey was readministered in 2023, with COVID-19 specific questions added. The preliminary analysis suggests that the COVID-19 pandemic impacted students’ judgement of credibility in health information sources. There were negative changes in the perceived credibility of family/friends, well-known websites, wiki, blogs/forums, and social media for both everyday life health and COVID-19 information from 2017 to 2023. Conversely, government/university, scholarly books/journals, and TV/radio all saw increases in perceived credibility for both everyday life health and COVID-19 information.

Drawing upon the communication privacy management theory, this study proposes a moderated mediation model to examine the links between privacy perceptions and user engagement in mobile health applications (mHealth apps). Through an online survey involving 1149 mHealth app users in China, results showed that social privacy concerns were negatively related to user engagement in mHealth apps, and perceived privacy of the app partially mediated this relationship. Moreover, perceived control positively moderated the indirect relationship between social privacy concerns and user engagement via perceived privacy. Finally, theoretical and practical implications are discussed.

This research investigates individualized information literacy instruction (ILI) for different student populations in higher education and its impact on engagement and learning outcomes (SLOs), specifically first-year students of color. The study is designed as a QUAL+quan convergent mixed-methods study, and will utilize critical race theory as its theoretical framework, as well as a participatory action approach. It is designed as a multi-session IL workshop series delivered outside of the traditional classroom, and is comprised of six one-hour sessions: an initial focus group, four IL sessions focusing on specific aspects of the research process, and semi-structured interviews. Data collected through discussions, open-ended worksheets with rubrics, and pre- and post-surveys will be analyzed to measure whether the instructional series impacted SLOs. The study is significant as it’s the first to specifically address the systemic racial achievement gap coupled with a multi-session IL workshop series, and can serve as a model for other institutions.

Data governance policy is of great importance for the development of digital economy. This paper proposes a four-dimensional policy mining framework to analyze the 1097 central data governance policies. We depict the development trajectory, analyze the policy subjects involved into the policy-making, trace the sources of policy, and characterize the policy tool structure based on the policy coding. We find that the core departments of data governance policy making need to strengthen the awareness of data governance; Policy-making should source enough convincing and authoritative policies to strengthen the long-term effectiveness and impact policies; There are imbalances and deficiencies of policy tool structure. It provides reference for other countries in data governance.