在即时消息应用中提供自动情感反馈的挑战
Challenges in Providing Automatic Affective Feedback in Instant Messaging Applications
摘要：
即时消息是计算机媒介通信的主要渠道之一。然而，人类通过基于文本的通信来理解他人的情感是非常有限的。为了将情感感知技术引入即时通讯，我们开发了一个系统，它可以自动检测最终用户在Facebook Messenger上收到的消息的情感，并相应地在他们的智能手机上提供彩色提示。我们在两周的时间跨度内对20名参与者进行了部署研究。在本文中，我们揭示了五个挑战，以及我们在基于用户反馈和聊天记录的研究中观察到的例子，包括（i）情绪的连续性，（ii）多用户对话，（iii）不同用户之间的不同动态，（iv）情绪的错误分类和（v）非常规内容。我们相信，这一讨论将有利于情感计算的即时通信的未来探索，也为会话情感感知的研究提供了启示。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
