Challenges in Providing Automatic Affective Feedback in Instant Messaging Applications
This work addresses the challenge of enhancing emotional awareness in instant messaging for users, but it is incremental as it focuses on identifying issues rather than solving them.
The researchers tackled the problem of limited emotional understanding in text-based communication by developing EmotionPush, a system that automatically detects emotions in Facebook Messenger messages and provides colored cues on smartphones, revealing five key challenges from a two-week deployment study with 20 participants.
Instant messaging is one of the major channels of computer mediated communication. However, humans are known to be very limited in understanding others' emotions via text-based communication. Aiming on introducing emotion sensing technologies to instant messaging, we developed EmotionPush, a system that automatically detects the emotions of the messages end-users received on Facebook Messenger and provides colored cues on their smartphones accordingly. We conducted a deployment study with 20 participants during a time span of two weeks. In this paper, we revealed five challenges, along with examples, that we observed in our study based on both user's feedback and chat logs, including (i)the continuum of emotions, (ii)multi-user conversations, (iii)different dynamics between different users, (iv)misclassification of emotions and (v)unconventional content. We believe this discussion will benefit the future exploration of affective computing for instant messaging, and also shed light on research of conversational emotion sensing.