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.

介绍了一种基于情感识别技术的即时通讯系统 EmotionPush，并通过部署研究发现了多个挑战，包括情感的连续性、多用户会话、情感分类的错误、用户在消息中表达情感的非传统方式，为即时消息的情感计算和情感识别研究提供了新的思路。

即时通讯应用中自动提供情感反馈的挑战

Challenges in Providing Automatic Affective Feedback in Instant  Messaging Applications

Instant messaging and push notifications play important roles in modern
digital life. To enable robust sense-making and rich context awareness in
computer mediated communications, we introduce EmotionPush, a system that
automatically conveys the emotion of received text with a colored push
notification on mobile devices. EmotionPush is powered by state-of-the-art
emotion classifiers and is deployed for Facebook Messenger clients on Android.
The study showed that the system is able to help users prioritize interactions.

EmotionPush 是一种基于情感分类器的系统，可以通过手机上带有颜色的推送通知自动传达接收到的文本的情感，并有助于用户优先处理互动。