Zhenhui Peng
ABSTRACT
Maintaining a positive group emotion is important for team collaboration. It is, however, a challenging task for self-managing teams especially when they conduct intra-group collaboration via text-based communication tools. Recent advances in AI technologies open the opportunity of using chatbots for emotion regulation in group chat. However, little is known about how to design such a chatbot and how group members react to its presence. As an initial exploration, we design GremoBot based on text analysis technology and emotion regulation literature. We then conduct a study with nine three-person teams performing different types of collective tasks. In general, participants find GremoBot useful for reinforcing positive feelings and steering them away from negative words. We further discuss the lessons learned and considerations derived for designing a chatbot for group emotion management.
- Saleema Amershi, DanWeld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, Paul N. Bennett, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, and Eric Horvitz. 2019. Guidelines for Human-AI Interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). ACM, New York, NY, USA, Article 3, 13 pages. https://doi.org/10.1145/3290605.3300233Google Scholar
Digital Library
- Sigal Barsade and Donald Gibson. 1998. Group emotion: A view from top and bottom. Research on Managing Groups and Teams 1 (01 1998), 81--102.Google Scholar
- Sigal G. Barsade. 2002. The Ripple Effect: Emotional Contagion and its Influence on Group Behavior. Administrative Science Quarterly 47, 4 (2002), 644--675. https://doi.org/10.2307/3094912Google ScholarCross Ref
- Sigal G. Barsade, Andrew J. Ward, Jean D. F. Turner, and Jeffrey A. Sonnenfeld. 2000. To Your Heart's Content: A Model of Affective Diversity in Top Management Teams. Administrative Science Quarterly 45, 4 (2000), 802--836. https: //doi.org/10.2307/2667020 arXiv:https://doi.org/10.2307/2667020Google ScholarCross Ref
- Alastair J. Gill, Darren Gergle, Robert M. French, and Jon Oberlander. 2008. Emotion Rating from Short Blog Texts. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '08). ACM, New York, NY, USA, 1121--1124. https://doi.org/10.1145/1357054.1357229Google ScholarDigital Library
- James J. Gross. 1998. The Emerging Field of Emotion Regulation: An Integrative Review. Review of General Psychology 2, 3 (1998), 271--299. https://doi.org/10.1037/1089--2680.2.3.271Google ScholarCross Ref
- Ari MJ Hautasaari, Naomi Yamashita, and Ge Gao. 2014. "Maybe It Was a Joke": Emotion Detection in Text-only Communication by Non-native English Speakers. In Proceedings of the 32Nd Annual ACM Conference on Human Factors in Computing Systems (CHI '14). ACM, New York, NY, USA, 3715--3724. https://doi.org/10.1145/2556288.2557215Google ScholarDigital Library
- J. Clayton Lafferty and Patrick M. Eady. 1974. The desert survival problem. Plymouth, Michigan: Experimental Learning Methods (1974).Google Scholar
- Gilly Leshed, Diego Perez, Jeffrey T. Hancock, Dan Cosley, Jeremy Birnholtz, Soyoung Lee, Poppy L. McLeod, and Geri Gay. 2009. Visualizing Real-time Language-based Feedback on Teamwork Behavior in Computer-mediated Groups. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '09). ACM, New York, NY, USA, 537--546. https://doi.org/10.1145/1518701.1518784Google ScholarDigital Library
- Moodbit. 2019. https://mymoodbit.com/ Accessed: 2019-04-03.Google Scholar
- Zhenhui Peng, Yunhwan Kwon, Jiaan Lu, Ziming Wu, and Xiaojuan Ma. 2019. Design and Evaluation of Service Robot's Proactivity in Decision-Making Support Process. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). ACM, New York, NY, USA, Article 98, 13 pages. https://doi.org/10.1145/3290605.3300328Google ScholarDigital Library
- Zhenhui Peng, Jeehoon Yoo, Meng Xia, Sunghun Kim, and Xiaojuan Ma. 2018. Exploring How Software Developers Work with Mention Bot in GitHub. In Proceedings of the Sixth International Symposium of Chinese CHI (ChineseCHI '18). ACM, New York, NY, USA, 152--155. https://doi.org/10.1145/3202667.3202694Google ScholarDigital Library
- Anthony T Pescosolido. 2002. Emergent leaders as managers of group emotion. The Leadership Quarterly 13, 5 (2002), 583--599.Google ScholarCross Ref
- Ross A. Thompson. 1994. Emotion Regulation: A Theme in Search of Definition. Monographs of the Society for Research in Child Development 59, 2/3 (1994), 25--52. http://www.jstor.org/stable/1166137Google ScholarCross Ref
- Carlos Toxtli, Andrés Monroy-Hernández, and Justin Cranshaw. 2018. Understanding Chatbot-mediated Task Management. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, Article 58, 6 pages. https://doi.org/10.1145/3173574.3173632Google ScholarDigital Library
- JOSEPH B. WALTHER. 1992. Interpersonal Effects in Computer-Mediated Interaction: A Relational Perspective. Communication Research 19, 1 (1992), 52--90. https://doi.org/10.1177/009365092019001003 arXiv:https://doi.org/10.1177/009365092019001003Google ScholarCross Ref
- Teng Ye and Lionel P. Robert, Jr. 2017. Does Collectivism Inhibit Individual Creativity?: The Effects of Collectivism and Perceived Diversity on Individual Creativity and Satisfaction in Virtual Ideation Teams. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17). ACM, New York, NY, USA, 2344--2358. https://doi.org/10.1145/2998181.2998261Google ScholarDigital Library
- Amy X. Zhang and Justin Cranshaw. 2018. Making Sense of Group Chat Through Collaborative Tagging and Summarization. Proc. ACM Hum.-Comput. Interact. 2, CSCW, Article 196 (Nov. 2018), 27 pages. https://doi.org/10.1145/3274465Google ScholarDigital Library
Index Terms
- GremoBot: Exploring Emotion Regulation in Group Chat
Recommendations
Making Sense of Group Chat through Collaborative Tagging and Summarization
While group chat is becoming increasingly popular for team collaboration, these systems generate long streams of unstructured back-and-forth discussion that are difficult to comprehend. In this work, we investigate ways to enrich the representation of ...
“Instant Happiness”: Smartphones as tools for everyday emotion regulation
Highlights- We investigated smartphone-based emotion regulation in daily life and its associated psychological consequences using experience sampling and qualitative ...
AbstractSmartphone use has become an indispensable aspect of daily life for billions of people. Increasingly, researchers are examining the impact of smartphone use upon psychological well-being. However, little research has investigated how ...
Persuasive Strategies and Emotional States: Towards Emotion-Adaptive Persuasive Technologies Design
Persuasive TechnologyAbstractTechnologies have been shown to alter how people feel and create outlets for expressing positive and/or negative emotions. This indicates that persuasive systems, which rely on persuasive strategies (PS) to motivate behaviour change, have the ...
Comments