Although group chat discussions are prevalent in daily life, they have a number of limitations. When discussing in a group chat, reaching a consensus often takes time, members contribute unevenly to the discussion, and messages are unorganized. Hence, we aimed to explore the feasibility of a facilitator chatbot agent to improve group chat discussions. We conducted a needfinding survey to identify key features for a facilitator chatbot. We then implemented GroupfeedBot, a chatbot agent that could facilitate group discussions by managing the discussion time, encouraging members to participate evenly, and organizing members' opinions. To evaluate GroupfeedBot, we performed preliminary user studies that varied for diverse tasks and different group sizes. We found that the group with GroupfeedBot appeared to exhibit more diversity in opinions even though there were no differences in output quality and message quantity. On the other hand, GroupfeedBot promoted members' even participation and effective communication for the medium-sized group.
|Title of host publication||CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems|
|Publisher||Association for Computing Machinery|
|Publication status||Published - 2020 Apr 21|
|Event||2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 - Honolulu, United States|
Duration: 2020 Apr 25 → 2020 Apr 30
|Name||Conference on Human Factors in Computing Systems - Proceedings|
|Conference||2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020|
|Period||20/4/25 → 20/4/30|
Bibliographical noteFunding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean National Police Agency and the Ministry of Science and ICT for police research and development (NRF-2018M3E2A1081492). We would like to thank Korea Creative Content Agency (KOCCA) for funding that partially supported this project. We also would like to thank Joseph Seering for extensive feedback on drafts. Finally, we would like to thank our participants for contributing to this study.
© 2020 ACM.
All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design
- Human-Computer Interaction