ReactionBot: Exploring the Effects of Expression-Triggered Emoji in Text Messages

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.