Conference Agenda (All times are shown in Mountain Daylight Time)

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 14: User Engagement and Experience
Time:
Monday, 01/Nov/2021:
4:00pm - 5:30pm

Session Chair: Janette Klein, University of North Texas, USA
Location: Salon B, Lobby Level, Marriott

As time permits, moderators will facilitate reflective discussions at the end of sessions! These will be opportunities to have extra discussion on key points, synergies, and provocative elements of the papers.


Show help for 'Increase or decrease the abstract text size'
Presentations
4:00pm - 4:15pm
ID: 117 / PS-14: 1
Short Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Social Media and Social Computing
Keywords: Social media image, User engagement, Machine learning, Regression analysis

Image Position and Layout Effects on User Engagement of Multi-Image Tweets

Xiaoyue Ma, Xiao Meng

Xi'an Jiaotong University, People's Republic of China

Current researches paid less attention to the image position and layout of tweets containing multiple images. Inspired by the research on user cognition, this study explored the impact of image position and layout on user engagement. The XGBoost model trained on single-image tweet data was used to predict the "user engagement potential" of a single image in multi-image tweets. Then, the influence of image position and layout on user engagement was analyzed through correlation analysis and OLS regression. It was found that the right position was more important in tweets with less than or equal to 4 images, and the position effects became symmetric with image adding. Layouts with 6 and 4 images had positive effects on user engagement, while layouts with 7 and 9 or more images had negative effects. This study provides insights into user engagement with social media images and may help improve interaction.



4:15pm - 4:45pm
ID: 193 / PS-14: 2
Long Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Human Computer Interaction (HCI)
Keywords: Human-computer interaction, subjective workload, gaze fixation, user-interface design, systematic review

A Mixed-Method Usability Study on User Experience with Systematic Review Software

Manhua Wang1,2, Selina Sharmin1, Mengqian Wang1, Fei Yu1

1University of North Carolina at Chapel Hill, USA; 2Virginia Polytechnic Institute and State University, USA

Systematic reviews are widely used in evidence-based medicine. Conducting a systematic review requires intensive mental efforts, especially during the study screening process. This challenge has motivated the development of intelligent software. This study examined and compared the performance, workload, and user experience of two systematic review tools – Colandr with AI features and Covidence without AI features by conducting a mixed-method usability study. The results showed that, compared with Covidence, Colandr helped reviewers with higher precision in citation screening. However, the user experience with Colandr was not optimal due to problems in its user interface design. Therefore, we suggest that the design and development of AI-enabled SR software emphasize the usability of the interface and apply user-centered design principles.



4:45pm - 5:15pm
ID: 111 / PS-14: 3
Long Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Library and Information Science
Keywords: Chinese painting and calligraphy, Digital archives search system, Information search process, Meaning making process, Search as learning

Learning Outcomes During Information Search in Digital Archives

I-Chin Wu1, Pertti Vakkari2, Bo-Xian Huang1

1National Taiwan Normal University, Taiwan; 2Tampere University, Finland

A museum’s digital archive system gathers information about cultural heritage and makes it accessible to the public. In this study we clarify the extent to which search behaviors reflect task outcome and foster users’ knowledge of painting and calligraphy. Ten users participated in this evaluation of the Digital Archives of Chinese Painting and Calligraphy Search System (DA-PCSS) of the National Palace Museum in Taiwan. Participants’ search activities and interactions with the DA-PCSS were recorded in two simulated tasks. The results show that participants who received high scores for their essays on the tasks formulated precise queries: instead of general terms they used precise expressions describing features in paintings and calligraphy. In addition, they were able to seek out sources to explore the topics. For such participants, a meaning-making process seems to have occurred during the search process. Our results suggest that the criteria for learning at various stages of search suggested by Vakkari (2016) seem to validly reflect the quality of the search outcomes. In all, the results elucidate how the evaluated system supports users as they search for target items, as well as how learning occurs during the search process and in turn influences task outcomes.



 
Contact and Legal Notice · Contact Address:
Privacy Statement · Conference: ASIS&T 2021
Conference Software - ConfTool Pro 2.6.143+TC
© 2001–2022 by Dr. H. Weinreich, Hamburg, Germany