Dystemo

December 26, 2016
Title: Dystemo: Distant Supervision for Emotion Recognition in Tweets
Dates: 2013 – 2016
Researchers: Valentina Sintsova and Pearl Pu
Keywords: emotion recognition, social media analysis, distant supervision, twitter
Abstract:

Emotion recognition in text has become an important research objective. It involves building classifiers capable of detecting human emotions for a specific application, e.g. analyzing reactions to product launches, monitoring emotions at sports events, or discerning opinions in political debates. Most successful approaches rely heavily on costly manual annotation. To alleviate this burden, we propose a distant supervision method—Dystemo—for automatically producing emotion classifiers from tweets labeled using existing or easy-to-produce emotion lexicons. The goal is to obtain emotion classifiers that work more accurately for specific applications than available emotion lexicons.

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