Learning Emotion Indicators from Tweets: Hashtags, Hashtag Patterns, and Phrases
Ashequl Qadir, Ellen Riloff · 2014
We present a weakly supervised approach for learning hashtags, hashtag patterns, and phrases associated with five emotions: AFFEC-TION, ANGER/RAGE, FEAR/ANXIETY, JOY, and SADNESS/DISAPPOINTMENT. Starting with seed hashtags to label an initial set of tweets, we train emotion classifiers and use them to learn new emotion hashtags and hashtag patterns.This process then repeats in a bootstrapping framework.Emotion phrases are also extracted from the learned hashtags and used to create phrase-based emotion classifiers.We show that the learned set of emotion indicators yields a substantial improvement in F-scores, ranging from +%5 to +%18 over baseline classifiers.