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Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
Paper Session 09: Human-Computer Interaction
Time:
Monday, 31/Oct/2022:
11:00am - 12:30pm

Session Chair: Alex Urban, University of Missouri, USA
Location: Rivers, Ballroom Level, Wyndham


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Presentations
11:00am - 11:30am
ID: 149 / PS09: 1
Long Papers
Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am22/submission-types-instructions/
Topics: Information Behavior (information behavior; information-seeking behavior; information needs and use; information practices; usability; user experience; human-computer interaction; human-technology interaction; human-AI interaction)
Keywords: Well-being intervention, conversational agent, voice user interface, adolescence, research methods

Measuring the Impact of Conversational Technology Interventions on Adolescent Wellbeing: Quantitative and Qualitative Approaches

Irene Lopatovska, Olivia Turpin, Ji Hee Yoon, Diedre Brown, Laura Vroom, Craig Nielsen, Kelli Hayes, Karin Roslund, Mary Dickson, Daniel Anger

Pratt Institute, USA

In order to help adolescents cope with loneliness during the social distancing and isolation imposed by the COVID-19 pandemic, we designed a conversational agent programmed to distract users from negative thoughts and advise them on strategies to improve their wellbeing. In order to assess the effects of the agent intervention on adolescent participants, we performed quantitative analysis of their self-reported mood states and qualitative analysis of their subjective views and opinions on the agent to help us understand their experiences. Trends in the quantitative data point to minimal changes in participants’ wellbeing and loneliness after interactions with the experimental agent. However, qualitative data on adolescent experiences suggests short and long-term positive effects of the experimental interactions. In reporting our findings, we aim to bring attention to the importance of the qualitative data for understanding human experiences with technology, as well as the limitations of the instruments developed in the field of psychology for human-information interaction research.



11:30am - 12:00pm
ID: 124 / PS09: 2
Long Papers
Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am22/submission-types-instructions/
Topics: Data Science; Analytics; and Visualization (data science; data analytics; data mining; decision analytics; social analytics; information visualization; images; sound)
Keywords: Data dashboard, COVID-19, information design, eye-tracking

User Perception and Eye Movement on a Pandemic Data Visualization Dashboard

Yu-Wen Huang, Yu-Ju Yang, Wei Jeng

National Taiwan University, Taiwan

This study utilized a two-phase user experiment to explore people’s perceptual and cognitive states interacting with the COVID-19 dashboard to obtain outbreak information. Specifically, 27 participants were assigned to interact with this dashboard with different color arrangements and performed image-memory, search, and browse visualization tasks sequentially. We found that the participants expected to obtain both global pandemic trends and single region/date statuses from the dashboard to help them grasp important information in the shortest possible time. They also allocated their attention differently to the dashboard’s content areas to match their individual visual movement and reading logics. Our participants indicated that the pandemic data visualization dashboard should use a principal-color selection that is alarming but without causing panic. In the study’s second phase, an eye-tracking experiment, it was found that the participants’ actual eye paths deviated from our expectations: clustering around headings and text, rather than on visualized charts or graphs as anticipated. Based on these findings, we provide design implications for builders of future data-visualization and disaster dashboards.



12:00pm - 12:15pm
ID: 219 / PS09: 3
Short Papers
Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am22/submission-types-instructions/
Topics: Information Behavior (information behavior; information-seeking behavior; information needs and use; information practices; usability; user experience; human-computer interaction; human-technology interaction; human-AI interaction)
Keywords: Humanoid robot; Human-robot interaction; Human factors; Robot personality.

The Influence of Personality Traits in Human-Humanoid Robot Interaction

Shih-Yi Chien1, Chih-Ling Chen1, Yao-Cheng Chan2

1National Chengchi University, Taiwan; 2The University of Texas at Austin, USA

With the advancement of science and technology, humanoid robots have been gradually adopted in human society. Given the human-like appearance, the perceived personality of a humanoid robot can affect humans’ general perceptions of the robotic agent, and even task performance. However, limited research pays attention to examining how a humanoid robot’s non-verbal cues characterize its personality traits. To solve this gap, this research aims to investigate how to use humanoid robots’ non-verbal features (textual and gestural information) to develop different kinds of personality attributes, and how these personality characteristics affect human-robot interaction. A total of 255 participants were recruited for this research, including pilot tests and two rounds of lab studies examining different levels of task complexity. The empirical results reveal the developed gestural cues allow a humanoid robot to distinguishably convey extrovert, ambivert, and introvert personality traits, where the perceived traits significantly affect user intentions to interact with the humanoid robot.



12:15pm - 12:30pm
ID: 255 / PS09: 4
Short Papers
Confirmation 1: I/we acknowledge that all session authors/presenters have read and agreed to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am22/submission-types-instructions/
Topics: Artificial Intelligence (machine learning; text mining; natural language processing; deep learning; value-sensitive AI design; transparent and explainable AI)
Keywords: explainable artificial intelligence/XAI, artificial intelligence explainability, public trust, organizational records management, informational 3rd party

Information Resilient Society in an AI World – Is XAI Sufficient? (2nd place best short paper award)

Sherry Xie1,2,3, Yubao Gao1, Ruohua Han4

1Renmin University of China, People's Republic of China; 2Center for Digital Records Management Research, People's Republic of China; 3Key Laboratory of Data Engineering and Data Knowledge of the Ministry of Education of China, People's Republic of China; 4University of Illinois at Urbana-Champaign, USA

This paper discusses the role of organizational records management (ORM) with respect to the field of explainable artificial intelligence (XAI) and argues about its necessity and significance. The current trend is to utilize AI to explain AI, including both explanation production and provision. We argue that this kind of approach is not sufficient by itself as it lacks neutrality and localness to explanation recipients, thus ineffective in establishing public trust. We propose the addition of the ORM profession, as an informational 3rd party, to the current and future XAI. We envision that, by working together with XAI performers, ORM contributes to an information resilient AI society. To take on the related responsibilities, the ORM profession must improve its professional expertise and strengthen its professional independence. We call for consensus among individual information professionals and the advocacy of information professional networks to make this vision a reality.



 
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