  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.
