ReactionBot
| Autor: | Gary Hsieh, Miki Liu, David B. Wang, Austin Wong, Ruhi Pudipeddi, Betty Hou |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Facial expression
Computer Networks and Communications Emoji media_common.quotation_subject 05 social sciences 050109 social psychology 050105 experimental psychology Human-Computer Interaction Nonverbal communication medicine Anxiety 0501 psychology and cognitive sciences Conversation medicine.symptom Computer-mediated communication Psychology Negative emotion Social Sciences (miscellaneous) Cognitive psychology media_common |
| Zdroj: | Proceedings of the ACM on Human-Computer Interaction. 2:1-16 |
| ISSN: | 2573-0142 |
| DOI: | 10.1145/3274379 |
| Popis: | In this paper we present ReactionBot, a system that attaches emoji based on users' facial expressions to text messages on Slack. Through a study of 16 dyads, we found that ReactionBot was able to help communicate participants' affect, reducing the need for participants to self-react with emoji during conversations. However, contrary to our hypothesis, ReactionBot reduced social presence (behavioral interdependence) between dyads. Post study interviews suggest that the emotion feedback through ReactionBot indeed provided valuable nonverbal cues: offered more genuine feedback, and participants were more aware of their own emotions. However, this can come at the cost of increasing anxiety from concerns about negative emotion leakage. Further, the more active role of the system in facilitating the conversation can also result in unwanted distractions and may have attributed to the reduced sense of behavioral interdependence. We discuss implications for utilizing this type of cues in text-based communication. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|