Conference Agenda (All times are shown in Mountain Daylight Time (MDT) unless otherwise noted)

Generative Artificial intelligence (GenAI) chatbots, e.g., ChatGPT, are emerging and gradually becoming pivotal tools in various domains, including libraries. Accordingly, AI literacy definitions, skills, and measures are developed. This research aims to delve into the various factors that are associated with librarians' AI literacy. The study measures included the AI literacy Scale and four sub-scales of AI Device Usage Acceptance (AIDUA): social influence, hedonic motivation, willingness to accept AI usage, and positive emotions toward AI. 107 librarians answered an online questionnaire. Findings reveal that librarians with high AI technology acceptance, which includes social influence, hedonic motivation, willingness to use AI, and positive emotions towards AI, tend to have higher AI literacy, suggesting that these factors can be utilized to promote librarians’ AI literacy.

Pew Research Center's findings reveal a notable trend: U.S. adults under the age of thirty exhibit a level of trust in information on social media that is comparable to their trust in traditional news outlets (Liedke & Gottfriend, 2022). This is particularly significant given the growing concern over misinformation, with a staggering 95% of Americans acknowledging its prevalence in society (Seitz & Fingerhut, 2021). To explore the factors influencing individuals' trust in information, researchers conducted a preliminary review of the literature, focusing on information science. This preliminary review identified seven major themes (health, politics & business, information sources, social factors, age groups, education & language, and privacy & security) that will guide a more extensive systematic review in the future. These themes provide valuable insights into the complexities of trust in information and should serve as a foundation for further investigation. Insights derived from this preliminary review are invaluable for scholars and practitioners seeking a deeper understanding of information trust dynamics. By illuminating these complex factors, this research lays the groundwork for future studies and interventions aimed at enhancing information trust among the general public.

This paper critically examines the intertwined history of statistics and eugenics through the work of Francis Galton, whose statistical inventions were guided by his problematic belief in eugenics. The paper highlights the historical development of regression analysis, arguing that acknowledging the discriminatory origins of this method is crucial for understanding historical and contemporary injustices in data-driven decision-making. The paper also considers the ethical implications of other statistical techniques, emphasizing the need for library and information science (LIS) students and practitioners to be aware of the societal implications of “objective” data analysis methods.

While research on how people identify deepfakes are emerging, there is currently a lack of focus on an important age group – seniors. We address this gap through a diary study to elicit seniors’ deepfake identification strategies. Results indicate that seniors performed well in identification performance and over time, the combination of strategies used increased in sophistication. Implications of our work are discussed.

This poster presents results from a phenomenological research study investigating the effects of a university consolidation on the affiliated libraries of three U. S. public university libraries. Semi-structured interviews were conducted through purposive sampling of twelve librarians working at three different consolidated institutions within the same university system. Data was analyzed through the lens of sensemaking theory, a process where individuals attempt to construct meaning and enact their roles within an organization through their evolving experiences (Ancona, 2011; Weick, 1995), and organizational theory which provides both a theoretical and practical way of managing, understanding, analyzing, and improving organizations based on patterns of design and behavior (Daft, 2001). The use of Bolman and Deal’s (1997) organizational theory, including the structural frame, the human resource frame, the political frame, and the symbolic frame, provides insight into the effects on library services and librarians’ identity resulting from consolidations.

The aim of the current study is to identify the dimensions of perceived online information quality and apply Q methodology to analyze users' perceptions both qualitatively and quantitatively. Data were collected from readers and contributors of English Wikipedia through two rounds of surveys. The analysis of the first round, with 197 participants, identified 36 dimensions of online information quality, while the second round with 68 participants yielded significant five factor categories of information quality with Q methodology. Q methodology was employed to configure the design and analysis of the second round of research, especially aiming to transform users' opinions and perceptions into more solid evidence.

Public library makerspaces aim to serve diverse groups of populations, but research on how to facilitate the participation of youth with disabilities is very limited. This study presents a case study of an exemplary public library that offers various activities and programming in its makerspaces for youth with disabilities. Our analysis shows different strategies used from the preparation step to reaching out and targeted programming in this case.

AI image generator, also known as Text-to-image generation (TTIG) technology, allows users to generate images based on natural language input. With advancements in AI, debates related to its application in the creative field have flourished. A systematic literature review was conducted to examine discourse that addresses the perception of people in the creative industry towards AI image generators and the impact of AI image generators on these individuals. The analysis of discourse revealed four major categories: 1) Evaluation of the product or outcome of AI; 2) Impact of AI on practitioners/artists; 3) Impact of AI on creative industry and society; 4) Capabilities of AI technology. Evaluation of the product or outcome of AI is discussed most frequently in the discourse, followed by the Impact on practitioners/artists. These findings provide insights into the areas of interest within AI image generator discussions on creative activity.

This narrative review synthesizes knowledge at the intersection of social media scholarship, the role of influencers in disseminating information about feminist causes. Feminist activism on social media, such as hashtag activism like #MeToo, has received much attention from scholars, but the role of influencers in disseminating information remains understudied. Much of the past research has examined the commercial nature of influencers. We conducted a narrative review using the search results from eight academic databases. We examined three research questions: (1) what types of social media influencers have been studied, (2) what feminist approaches were drawn on, (3) and what are influencers’ functions in the dissemination of information on feminist causes. We found that the literature had covered influencers from many parts of the world whose content focuses on various areas of life, with some specifically advocating antifeminism. We also found that feminist theoretical approaches, mainly surrounding neoliberalism and post-feminism, have informed much of this research. Finally, we found that the studies within feminism as challenging norms and expectations, calling out social issues, and building community. From these findings, we derive directions for future studies and the continuation of our project.

This poster aims to conduct an examination of the applications of Artificial Intelligence (AI) in oncology. We collect projects from National Institutes of Health (NIH) which delve into how AI applications and techniques are used in cancer research between 2018 to 2024. Results show AI’s ability to enhance lung and pancreatic cancer through novel imaging techniques and data processing. We find that refined medical imaging can be done with AI-driven techniques such as machine learning or deep learning to improve diagnostic accuracy potentially leading to better survival rates for patients involved. Additionally, this reveals how AI transformed oncology studies underlining the movement toward complex diagnostic algorithms that allow accurate stage assignments. Consequently, these forms of teamwork are essential when determining as well as making reliable Cancer care systems by developing strong AI systems with interpretation abilities using supportive NIH funding.

When a serendipitous discovery is made while searching within a digital library collection (such as an academic digital library at a university), the searcher has a difficult choice to make: either pursue the serendipitous discovery or set it aside and deal with it later. If they take the first option, this breaks the flow of the primary search activity which may make it difficult to resume. If they take the second option, they may have difficulty re-finding what they discovered when they are finished with the primary search activity. We have developed a novel search interface that includes topic-based workspaces and a “read it later” list. Serendipitous discoveries can be easily added to the “read it later” list, allowing the searcher to stay focused on their current search activity knowing that they can easily return to the discovered resource. For each resource saved to the “read it later” list, a textual similarity is calculated against the collection of documents saved in each of the searcher’s workspaces. This allows them to easily identify which of their prior search tasks is a best fit for the discovery, as well as an ability to create a new workspace if desired.

Despite the growing interest in leveraging Large Language Models (LLMs) for content analysis, current studies have primarily focused on text-based content. In the present work, we explored the potential of LLMs in assisting video content analysis by conducting a case study that followed a new workflow of LLM-assisted multimodal content analysis. The workflow encompasses codebook design, prompt engineering, LLM processing, and human evaluation. We strategically crafted annotation prompts to get LLM Annotations in structured form and explanation prompts to generate LLM Explanations for a better understanding of the LLM and transparency. To test LLM's video annotation capabilities, we analyzed 203 keyframes extracted from 25 YouTube short videos about depression. We compared the LLM Annotations with those of two human coders and found that LLMs have higher accuracy in object and activity Annotations than emotion and genre Annotations.

Between 1996 and 2018, there was little federally funded research on gun violence, even though it remains a perennial issue, resulting in considerable loss of life. Advocacy and academic groups piece together data to conduct their research, but the U.S. firearms data infrastructure is flawed. A current project spearheaded by the Inter-university Consortium for Political and Social Research (ICPSR) and researchers at the University of Michigan aims to confront that problem. This Quality Improvement study seeks to uncover the information needs of researchers in firearm injury prevention and community-based interventions through interviews with public health and medical researchers. Interviews with researchers reveal problems associated with established knowledge and data infrastructures. Using infrastructural inversion as a method, we find scattered data and lags in public health data availability. Data harmonization is crucial for researchers and data warehouse managers.

This project explores the intersection of local and online discourse around book bannings using the McMinn County School Board’s decision in 2022 to remove Art Spiegelman’s graphic memoir, Maus, from their school curriculum as a case study. Through interviews with McMinn County residents and data collected from Twitter, I argue that social media has altered book banning discourse. I interviewed 10 residents and asked them to discuss their experiences when Maus was removed by the school board and to reflect on how the local community responded amidst worldwide scrutiny online. Discourse on Twitter involved collecting over 2000 tweets mentioning the @McMinnCountySch account and tweets discussing Maus to understand online responses to the board’s decision. I use Danielle Allen’s discourse flow model as the theoretical framework for this project. In my initial findings, discourse began at the local level before traveling online and then back into the local space. Ongoing data analysis has shown that locally, residents were concerned with the board’s decision along with the perception of their community once news of the banning spread. This is supported by Twitter discourse, where many tweets cast the McMinn County community in a negative light based on the school board’s actions.

Connecting the conference theme “Putting People First: Responsibility, Reciprocity, and Care in Information Science Research and Practice,” this research emphasizes the importance of centering our participants, their experiences, and their well-being. While Information Science (IS) researchers and practitioners aim to understand information seeking and needs across vulnerable communities, this poster suggests using “the vulnerable observer” (Behar, 1997) as a framework to encourage IS researchers to acknowledge and evoke the researcher’s own emotional involvement with their participants. Through the study of vehicle residents’ information practices as a case study, this work draws on various ethnographic methods, paired with information horizon interviews with 22 participants, utilizing trust, reciprocity, and positionality as tools to introduce the researcher’s own vulnerability when working with vulnerable populations. Preliminary findings highlight participants’ communities as valuable information sources some of the most emotionally vulnerable parts of participants’ conversations which impact their information seeking practices. A brief conclusion reiterates the importance of building deep rapport with vulnerable participants.

In 1927, an organized group of Black college and graduate students from the Washington Intercollegiate Club of Chicago compiled a rich informational reference text reflecting the mosaic of Black life in Chicago, IL, USA. This effort resulted in the publication of two editions of the Intercollegian Wonder Book in 1927 and 1929. These books are reflective of the New Negro movement and cultural renaissance of the Black urban population in the early 20th Century. Our project examines the influence of the Wonder Books through methods that express the layered informational context of a Black community. The poster reflects the iterative development of a phased descriptive, archival, data and visual analysis of an historic Black Community. such as citation tracking, genealogical research of individual members, and analysis of data usage by the club's active students.

KEYWORDS

Archives, Citation Analysis, Data Visualization, African Americans, Information History

This poster explores how BookTok, a social media community on TikTok focused on literature, builds a community among an audience of primarily female readers, sometimes called “fangirls.” The researchers analyzed comments on popular BookTok videos, finding that emotional responses, generic comments, and seeking interaction with other viewers were most prevalent. BookTok discussions prioritize shared experiences and emotional connection over critical analysis, creating a welcoming space for readers of all ages. This research suggests that BookTok functions similarly to traditional book clubs, offering a platform for community building and potentially boosting reading engagement and offers possibilities for engagement for libraries and educators.

North Carolina Central University (NCCU) is dedicated to addressing the pervasive issues of digital inequality prevalent in Durham’s underserved anchor communities through the Digital Equity Leadership Program (DELP) and NCCU’s School of Library and Information Sciences (SLIS). DELP offers a holistic approach as its activities and initiatives encompass workforce development, technological access, and digital literacy training, leveraging its partnerships with local organizations. DELP fortifies communities through its holistic initiatives and adopts an innovative approach to fostering long-term community resilience and adaptability in an ever-growing digitized economy. DELP amplifies capacity building through multifaceted employability and economic growth approaches, laying the groundwork for a more equitable and sustainable future. DELP’s core activities expose our community members to skills that support their financial, economic, health, and digital equity. By bringing together program partners and our resources, capabilities, and expertise in digital literacy, innovative remedies were created to reach deeper into the surrounding communities.

This study investigates the role of trust in human-AI collaboration in K-12 education, focusing on generative AI. Using a two-factor experimental design (n = 26), we examined attitudes toward AI and creativity level as independent variables and assessed cognitive trust, affective trust, perceptions of usability, and continuance intention to use generative AI tools in text-to-text (ChatGPT) and text-to-image (Canva) tasks. The results is analyzed with two-way ANOVA, we find that: (1) text-to-text human-AI collaboration tends to foster higher emotional engagement and trust compared to text-to-image human-AI collaboration; (2) perceptions of usability and continuance intention to use are slightly higher in text-to-text interactions, suggesting a preference for text-based generative AI tools; (3) significant interactive effects between attitudes toward AI and creativity were observed across all measured variables, highlighting the importance of considering both factors in understanding and improving human-AI collaboration in educational settings, contributing to research on generative AI for learning assistance.

Climate change is a polarized topic on social media in the U.S. Actors who advocate climate change as scientific fact, or tout it as a conspiracy, both post videos on YouTube. Both kinds of videos can receive millions of views and thousands of comments. Given the polarized nature of the topic, we might expect a high degree of vitriolic speech in the comments around the videos. Previous Twitter studies would also suggest significant differences in the networks made from the interactions of such comments and replies. This study focuses on these comments and replies in an effort to understand the nature of discourse surrounding climate change believer and skeptic videos. Our hope is to extend the existing literature studying scientific communication around climate change, which to our knowledge hasn’t specifically compared discussions around both climate change believers or skeptics on YouTube. Results show most users only comment on other users that align with their own perspectives about climate change, and express positive sentiment toward them. Our study also finds that the more negative the users’ comment, the more connections they have with other users. These findings indicate further investigations of climate change social activities on YouTube.

The current study aims to explore college adjustment and information experiences of first-generation college students in coursework and extracurricular learning contexts. Information World Mapping visual-elicitation interviews were conducted with 25 first-generation college students from two elite universities in one university system. We found that while first-generation college students tend to feel fallen behind, and be somewhat remote from professors and peers, they make use of all resorts to thrive in both coursework and extracurricular learning experiences. Most of their personal-meaningful coursework experiences are academic group work; their extracurricular learning experiences are career-oriented. Implications were discussed based on the findings.

This study is a project designed to be part of the PhD dissertation research as a pilot aimed at assessing the study’s feasibility and its potential for refinement. The paper presents a study that explored the attitudes and knowledge of college students toward privacy in TikTok. This paper aims to comparatively assess student privacy literacy and privacy-related concerns along with their response patterns towards the Florida State University policy banning TikTok on campus networks. The study utilizes semi-structured, qualitative interviews to collect data from five undergraduate students (age 18–24) at Florida State University. It has analyzed and discussed the data collected from these interviews to achieve greater insight into the privacy literacy of students, their privacy concerns, and how Generation Z (Gen Z) students view institutional policies affect their use of social media. Preliminary findings suggests students are skeptical of the ban due to perceived ineffectiveness of the school policy. Analysis showed the new school rules had little effect on students' usage pattern or the amount of time they spent using TikTok.

The introduction of ChatGPT has sparked significant interest and presented both great opportunities and challenges to higher education. While more students are using ChatGPT, little is known about their mental models for and sensemaking of the system, including the metaphors they use to understand the system. In this exploratory study, we interviewed 25 students at three universities in the US during the summer of 2023 to identify the metaphors they use for ChatGPT. Through qualitative analysis of the interview transcripts, we found that participants commonly used metaphors to make sense of ChatGPT. They compared ChatGPT to humans and popular technologies or tools, with being the most frequently Google mentioned. These findings highlight the potential for metaphor-based design and the development of AI literacy programs.

Community partnerships with libraries, archives, and museums are increasingly recognized as essential to developing and stewarding complete, accurate, and equitable digital cultural records. While research and practice in this area has burgeoned, there is limited empirical research characterizing the state of the field. This study offers preliminary findings of a systematic, state-of-the-art review of community-institutional partnerships in digital cultural heritage collections and initiatives. This review systematically identifies wide-ranging, active community partnerships among relevant institutions, along with analysis of the high-level objectives of partnerships, and the array of approaches taken in pursuit of those objectives.

Modern democracy often requires citizens to engage in policy debates demanding multidisciplinary knowledge. This can lead to a cognitive gap that urges citizens to seek information for decision-making on unfamiliar policy issues. The credibility of this information is crucial, as it shapes individual perceptions and attitudes, which aggregate as public opinions. To deepen the understanding of information credibility, this study proposes an experiment leveraging theories of the continued influence effect and the illusory truth effect to answer how initiative and repetition of exposure influence the evaluation of information credibility. 1,400 participants will be recruited and requested to rate the credibility of opposing arguments regarding a fictitious referendum provided with varying orders and numbers. The result is expected to show a positive causality between exposure initiative, information repetition, and information credibility. The findings will aid in promoting well-informed democratic deliberation in an era of political polarization.

Although the discussion about conversational agents is inevitable, the question arises whether this theoretical and practical topic is starting to roll within the Library and Information Science (LIS) community. This poster submission is interested in providing a first insight into the current LIS research activities, focusing on the publication sources selected by the authors. For this purpose, the databases Scopus and Scimago Journal & Country Rank (SJR) were used. Of the initial LIS publication sources (N=271), about 27% of the sources accepted research articles by authors are about conversational chatbots.

One of the key aims of information search tools is to organise information and make it accessible and useful, reducing the chaos of an information deluge to ten blue links, perhaps with some context about the utility of the information they represent. Generative AI answer engines, such as ChatGPT, have gone one step further, reducing the ten blue links to a single passage of text: highly digestible, easily accessible, possibly false and ultimately bland. All chaos, including disagreement between sources, possible false information, and the influence of societal biases, and the opportunity to access more information is hidden under a rug of simple, authoritative sounding text. Friction, disagreement, reflections and odd informational juxtapositions have long been known to underpin serendipity, inspiration and creativity, yet these answer engines reduce all of these opportunities, particularly in the context of complex information needs. Using 'bounded chaos' as a framework, we critique the trade-offs made by answer engines, demonstrating that, even as they are non-deterministic, they hide the wrong parts of the chaos for those who seek learning or inspiration. We make the case against bland, and defend information seekers need for perceptible heterogeneity, friction, and even a little chaos.

The Information Science/LIS research community welcomes research across the methodological spectrum, including qualitative methods featuring human subject research. This poster presents the research design and data collection process for an exploratory study examining qualitative research published as both long and short papers in ASIS&T Annual Meeting proceedings from 2018-2022.

Research teams naturally appear from long-term collaborations. However, effectively tracking their evolution, showing cross-team participation, and defining team activity periods pose significant challenges. To address these issues, we propose an innovative method involving the computation of an annual active index for each researcher. We applied our method to analyze the solid-state battery domain. Leveraging co-inventor relationships, we found 246 teams, categorized into three groups based on their size. Approximately one-third of these teams drive technological development, with more than half of the members taking part in multiple teams simultaneously.

We describe a project in which we develop a text-based measure of HI in the context of scholarly communication using corpora of scientific publications. The data and analytic approach we use will circumvent known concerns with self-reported data on humility levels and will be calculable on a large scale. We use a computational grounded theory approach to develop a text-based measure of HI. We draw from an annotated corpus of scientific articles in economics, psychology, and sociology (2010-2023), generating three supra-dimensions of HI (Epistemic, Rhetorical, and Transparent) and several novel sub-codes of HI. We present our initial analysis with a focus on the three dimensions of HI derived from a computational grounded theory approach. The text-based measure will be used to help us better understand how contextual factors shape HI and contributes to mixed methods in information science research.

Many of the biggest issues facing public health today focus heavily on information, yet few information scientists work directly on applied public health problems. While health informatics has a rich history in LIS, for information scientists who want to work on applied public health issues, mentorship has been ad hoc and cross-training pathways individually forged. With funds from the Public Health Agency of Canada and Canadian Institutes of Health Research, the Public Health Information Science Initiative (PHISI) will increase information science capacity in applied public health internationally. The PHISI will involve three one-year mentoring cohorts of emerging information scientists interested in conducting applied public health research, with an emphasis on population health information intervention research Initial plans are to hold a pre-conference training workshop to launch each cohort, with webinars and individualized mentoring throughout the year. By taking the mutual mentoring approach identified as especially effective for supporting under-represented early-career scholars, the PHISI will benefit both early-career information scientists and the established public health and information scientists who participate. This poster provides an interactive opportunity for conference attendees to make suggestions, ask questions, and directly influence the shaping of the first PHISI cohort.

The introduction of the Association of College and Research Libraries’ (ACRL, 2016) Framework for Information Literacy for Higher Education, or “the Framework,” has fostered efforts to apply the document’s concepts to information literacy instruction (ILI) to meet the needs of post-secondary students across faculties. However, little research has directly compared students’ perspectives on the Framework’s concepts by discipline. This poster presents findings from a larger, mixed-methods project investigating student perspectives on the Framework in which participants in the faculties of arts (n=123) and science (n=90) expressed distinct views and rankings. Their perspectives particularly diverged around perceived roles in assessing the authority of information sources and how “relevant to their experience in school” they found most Framework frames. This project expands upon emerging learner-centered research aiming to meaningfully improve Framework-based ILI through its direct disciplinary comparisons and use of the recently developed Information Literacy Reflection Tool (ILRT; Robertson et al., 2022).

Even as the number of doctoral students reporting mental health challenges continues to grow, many students who experience significant mental distress do not seek treatment for these concerns. To explore this phenomenon, thirty semi-structured interviews were conducted with doctoral students at a large U.S. public university. This poster reports on a candidate theme from a larger qualitative analysis that explored the barriers doctoral students face when seeking mental healthcare on-campus. Insights from the theme “minimal institutional support” are presented here, and discussed with respect to health literacy, information marginalization, and consumer health information justice.

This study investigates various types of situational relevance as assessed by students in the context of AI-generated responses for educational purposes. Data were collected through interviews with four undergraduate students, and a qualitative research method was employed to analyze data. The findings reveal the specific roles of AI chatbots concerning students' tasks and types of situational relevance. The research highlights differences between system inefficiencies and students' coping behaviors in situational relevance types, providing implications for future research.

Canvas, a learning management system (LMS), has been widely adopted by academic institutions across North America. Despite its robust features, the user experience with Canvas varies significantly. This study examines the design of a Canvas course website, providing evidence-based guidance for creating user-centered LMS interfaces. The findings aim to enhance the user experience by addressing issues such as information overload, user control, and accessibility. Design principles and recommendations generated from this study are crucial for our institution-wide adoption of Canvas, promoting a seamless and supportive learning environment.

Medical evidence on the risks and benefits of cannabis is limited; existing research is often inconclusive or conflicting. In the United States, cannabis use during pregnancy is stigmatized and often subject to complex legal constraints; these contextual components may have significant effects on information seeking and informed decision-making processes. This study applies reflexive thematic analysis to 23 telephone interviews with individuals considering cannabis use in pregnancy or lactation to explore their information needs; how adequately those needs were met; and how information triangulation, and other information seeking behaviors, were used to make decisions given the dearth of scientific evidence. Findings suggest that information needs are complex and contextual, and that participants used forms of triangulation that included relational and intuitive elements as well as cognitive assessment processes. A new model of Everyday Triangulation (ET) is presented to represent these complex assessment practices in a holistic manner.

Traditional roles of Japanese prefectural libraries involve supporting and advising municipal libraries. However, since the 2000s, their roles have diminished owing to financial downturns, an aging population, and municipal libraries’ establishment, forcing them to redefine their missions and services to remain relevant. This study aimed to determine whether differences exist in the services of prefectural libraries based on the varying status of municipal libraries and to illustrate these differences through case studies on a pilot basis. The following three research questions were posed: (1) Do differences exist in the services provided directly to citizens? (2) Do differences exist in the services provided through municipal libraries? (3) Do differences exist in the services supporting municipal libraries? Using hierarchical cluster analysis, Tokyo and Hokkaido were selected for a comparative case study. The findings indicate significant differences in services, influenced by establishment rates and service levels among municipal libraries.

Brenda Dervin’s Sense-Making Methodology has had a significant impact on communication, information science, and other fields, with over 18,800 citations on Google Scholar. Researchers over the years, including a recent ARIST review, have studied Dervin’s work. However, prior research has not analyzed a single article to see how it has been cited over the years across different fields. In this study, we examine 50 of the 1,766 articles published after the year 2000 that cited her 1983 paper. The research question investigated is, “What is the impact of Dervin’s Sense Making Methodology in the twenty-first century in fields outside of information science?” We found that sense-making has been applied to social media, academia, and health information seeking, among other related fields. The findings should be useful to scholars interested in information science and methodology. The study also shows that information science is not a siloed field and impacts other fields.

Digital interfaces serve as gateways to information, and web accessibility is the key to fostering equity in these spaces. This paper comprehensively analyzes web accessibility on library webpages across Connecticut public colleges (USA). With the most recent publication of Web Content Accessibility Guidelines (WCAG) being published in 2023, there is limited research available about how academic libraries meet these new standards. By employing a systematic methodology, this study examines the accessibility features and barriers presented on these webpages. The research was completed using manual checks for the 80 of the 86 WCAG 2.2 level AAA standards. The quantitative data was analyzed to provide a nuanced understanding of the current state of digital inclusivity in academic library websites. The findings of this research shed light on the prevalent accessibility gaps and offer insights into potential strategies for enhancing web accessibility practices for academic institutions. This study contributes to the ongoing discourse on digital inclusivity and underscores the importance of prioritizing accessibility initiatives to create more equitable digital environments for all users.

The newest editions of generative AI (GenAI) tools demonstrate profound capabilities that promise to reshape education. It is of vital interest to determine how these applications will modify how the public perceives and interacts with history, as well as how history education is delivered. In this poster, we investigated academic historians’ practices and perceptions of integrating GenAI into their teaching. We conducted semi-structured interviews with six historians who teach university-level courses. We identified the major concerns and perceived benefits of GenAI integration in history education, and some typical uses of GenAI in history classes. Our work contributes an important baseline assessment of attitudes and practices within the field so that we may better understand the existing gaps among academic historians and the extent of those gaps.

3D data creation methods and virtual reality (VR)-based visualization techniques are increasingly common in interdisciplinary research and pedagogy. 3D data represent a new challenge to existing digital curation frameworks for academic libraries and other support institutions. This poster describes the research methodology, background, and research plan for an in-progress, 3-year project funded in part by the Institute of Museum and Library Services (IMLS) (grant #: LG-254830-OLS-23). This project is exploring 3D data creation and curation practices of researchers across a range of 3D creation modalities and disciplines.

In cultural heritage crowdsourcing, imbalanced volunteer task choices can impact project completion rate and sustainability. Nudges offer a way to alleviate this imbalance. This paper proposes three nudges: task order, visual saliency, and feedback based on dual-process theory. We conducted a 2×2×2 factorial experiment incorporating eye-tracking research methods to investigate how these nudges affect volunteer task choices. The results demonstrate a significant positive impact of visual saliency. While task order and feedback did not demonstrate significant effects, eye-tracking results reveal that they effectively captured participants' attention. Our findings suggest that designing platforms with nudges could address the issue of imbalanced task choices in cultural heritage crowdsourcing projects.

Despite the growing emphasis on artificial intelligence (AI) education, there is relatively little research on the motivational factors that influence students' intention regarding AI knowledge acquisition and the utilization of AI applications. Understanding these factors helps educators and researchers to develop appropriate interventions to promote AI education. Guided by expectancy-value theory and theory of planned behavior, we examined how university students' beliefs influenced their motivation to learn about and engage with AI technologies. Our findings demonstrated the significant role of expectancy-value beliefs in shaping students’ behavioral intention. Additionally, we identified gender differences, which can inform educators in designing gender-specific interventions to enhance female students’ motivation in AI learning.

This study explores a case of anime dropout/disengagement to understand media information users. Particularly, this study identifies elements in anime (e.g., Tropes) that prevent audience from continue watching what they had started (i.e., dropout/disengagement). A content analysis of 226 posts from MyAnimeList.net, an online anime database and fan community, suggests that the major elements that motivate audience dropout are Plot/Narrative, Tropes, Artwork/Visual Style, Characters, and Mood. The expectation gap and sunk cost also contribute to disengagement. This study presents a way to enrich anime metadata through analyzing the identified elements. Additionally, this study suggests that understanding anime disengagement may contribute to the search and recommendation of anime.

Globally, approximately 50 million people live with dementia, a number projected to exceed 152 million by 2050 according to Alzheimer’s Disease International. Recent studies reveal that individuals with dementia, including Alzheimer's disease (AD), exhibit positive responses to familiar music, potentially reducing agitation, depression, and stress. However, traditional methods of identifying music preferences in dementia patients, such as questionnaires and interviews, are cumbersome. This paper explores a novel approach utilizing a minimal user-interface music player prototype for smart devices. Using the music player prototype, facial expressions of participants (Germany, and South Korea) age 65+ were recorded while listening to music to detect a song preference. Although participants did not have diagnosed dementia, they exhibited age-related memory loss, serving as proxies for testing. Results suggest the feasibility of automated music preference detection, eliminating the need for traditional input methods like personal information or keyword searches.

Individuals with polycystic ovary syndrome (PCOS) turn to Instagram influencers as an alternative or complementary PCOS information source to their physicians. However, ambiguous qualifications of influencers, and contradicting claims regarding how to manage the condition, make it difficult to identify credible sources. Using a directed qualitative content analysis, we examined the range of strategies that 10 Instagram PCOS influencers used to signal credibility. We found that influencers utilized three source credibility strategies. A key contribution of the study is a description of how PCOS influencers reference sources to signal credibility. Following a discourse analysis, we found that Instagram PCOS influencers discuss what it means to be healthy with PCOS, and how they contribute to a wider cultural participation in healthism. The findings build upon the source credibility literature to identify novel credibility cues used by influencers as social media platforms evolve, and further, reveal the underlying healthism-centric rhetoric by PCOS influencers.

The study proposes and describes a novel system called the Health Data Exchange. HDX is useful for identifying relevant experts in healthcare based on specific skill sets and their cohorts. Initial experience suggests that an expert database based on biographical data can be developed. Several techniques for automatically identifying the critical data, data normalization, storage, and retrieval are described that supported the development of the system. Such a system has the potential to facilitate efficient search and foster global collaboration among healthcare experts.

Despite global recognition of health as a fundamental human right, disparities persist due to gaps in Health Insurance Literacy (HIL). This study investigates HIL among young adults, focusing on their search behaviors and the impact of Search Generative Experience (SGE) and Generative AI. Participants displayed skepticism towards sponsored ads, preferring unbiased sources on government websites. Brand familiarity, notably with Blue Cross Blue Shield (BCBS), also influenced decision-making. Engagement with SGE for simplified explanations suggests its potential to impact HIL. Transparent and user-centered interventions are crucial for improving HIL, contributing to more informed healthcare decisions and reduced disparities in access to care.

This study evaluates the usefulness of heatmaps in understanding user preferences during book selection in online book discovery platforms. Based on user interactions with two book overview pages, it compares heatmaps generated from user clicks and eye-tracking data to identify key metadata influencing readers’ choices. Initial results indicate that click-based heatmaps can be a useful tool for this type of investigation, especially considering the cost of eye-tracking where heatmaps are typically generated.

This poster investigates how ACRL award-winning libraries address generative AI literacy in their libguides. Using the ACRL "Framework for Information Literacy for Higher Education," we analyzed newly created guides from 28 libraries. We found that this framework could serve as a foundation for AI literacy. The coding scheme developed from this analysis can be used as a reference for librarians when planning instruction or creating libguides. In addition, we identified common strategies and literacy components that librarians emphasize at this stage.

The data-intensive research paradigm is sweeping through the scientific community, and new interaction challenges for interacting with data have emerged. Data reuse emerges as a critical driver of human-data interaction, positioning data repositories at the forefront as the optimal solution for facilitating this process. This study adopts a diary study methodology to analyze the data repository-supported human-data interaction behaviors driven. The findings reveal that human-data interaction extends beyond mere engagement with data, encapsulating elements of human-computer interaction, engagement with literature, interactions with agent systems, and interpersonal communication.

Machine learning (ML) models for deepfake detection are important for countering the threat of such videos. However, human detection is also critical because automated approaches may not always be available to people online. This study compares ML models versus humans for deepfake detection, using a selection of real and fake videos obtained from the Web. Results surprisingly showed that humans performed better. Implications of our work are discussed.

In academic literature, the semantic evolution of scientific terms reflects the development of domain knowledge. While there have been studies using diachronic word embeddings to reveal cultural and social changes, research on the semantic evolution of scientific terms remains limited. This paper proposes a method utilizing diachronic semantic vectors to elucidate the semantic evolution of scientific entities. Firstly, diachronic semantic vectors of entities are trained using incremental learning to compute the semantic transition (ΔA) of a given entity A between periods t1 and t2. Secondly, entities similar to ΔA in periods t1 and t2 are defined as leading reasons and accompanying reasons, respectively. The experiment result shows that the leading reasons can capture the changes of entities in the nascent stage, and the accompanying reasons can capture the changes of words in the mature stage. The proposed method offers a better quantitative insight into the details and reasons behind domain knowledge evolution.

Prior research suggested the empirical approach to indexing for fine arts based on users’ search queries. This study examined the characteristics of user queries submitted to the library catalog of a fine arts academy, and compared users’ search terms with controlled vocabularies to assess their levels of matching. Based on search-log analysis, this study identified eight categories of user queries and 10 subcategories, indicating that the information needs of the fine arts community are diverse in language and culture and focus on named entities, disciplines, and various types and levels of fine arts. The mapping between user queries and controlled vocabularies found that around 20% of user search terms were non-matching. Based on the findings, this study provided suggestions for improving the search functions of library catalogs and enhancing controlled vocabularies to support the retrieval of fine arts monographs.

This study aims to compare the information literacy education practices of university libraries in Taiwan and South Korea using the Framework for Information Literacy for Higher Education (ACRL, 2016). The result shows that while Taiwanese institutions demonstrate comprehensive coverage across all six frames, South Korean university libraries lack some frames. The identified gaps will be analyzed thoroughly with ongoing research. This research will contribute to understand the shortcomings in the information literacy education provided by university libraries and suggest how we can further research and improve in the future.

Environmental sound recording is increasingly vital to the production of scientific and ecological information and knowledge. While research applications have grown tremendously, there is a lack of empirical research around the practices and experiences of those responsible for creating and managing these recordings. This poster reports on initial findings of a qualitative research project that interviewed 30 academic and professional researchers from across Canada and the United States, exploring information activities and meaningful elements and actors involved in their interactions with environmental sound recording. From preliminary findings, two themes are discussed: sound and listening skills involved in the creation and analysis of environmental sound recordings are complex, multisensory information practices, and changing environments and technological affordances enable and constrain the seeking and sharing of information and resulting knowledge production.

This research examines how female college students interact with various types of information in the social practice of job seeking in Japan. Qualitative analysis of semi-structured interviews with female college students reveals how they sift through abundant information during this process, which puts them under considerable pressure. Considering their prospects as women in the workplace adds another layer to the factors influencing their interaction with information during job search. Their information activities involved internal mediation between the information and experiences they gain and their own understanding of themselves regarding the goal of their job search, which can change over time. They come to terms with their results by making sense of or accepting their decisions. This study offers practical insights for designing more effective support for students.

Given the increasing prevalence of patrons with diverse social, physical, and psychological needs, public libraries are beginning to explore ways to address these community needs by offering social services. However, questions remain about whether social services should be part of the library's service domain and how libraries can effectively fulfill these needs. This poster presents insights from community members and librarians on the relevance of integrating social services into library missions, offering implications for a potential library social service.

Early publishing, or preprints/e-preprints, is the practice of making research available before formal publication. This research examines early and non-early publications in Library and Information Science, focusing on trends, citation impact, obsolescence, and time lag. It reveals an upward trend in early publications, which, despite their lower quantity, have a higher citation impact. Early publications also demonstrate a longer citing half-life, indicating their sustained relevance. Analysis of time lags reveals that about 49.25% of early publications are formally published within three months, with 75.5% published within six months, and only 5.66% taking more than a year. These findings underscore the importance of early publication in enhancing research impact and visibility.