Paper: Generating a Word-Emotion Lexicon from #Emotional Tweets

ACL ID S14-1002
Title Generating a Word-Emotion Lexicon from #Emotional Tweets
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

Research in emotion analysis of text sug- gest that emotion lexicon based features are superior to corpus based n-gram fea- tures. However the static nature of the general purpose emotion lexicons make them less suited to social media analysis, where the need to adopt to changes in vo- cabulary usage and context is crucial. In this paper we propose a set of methods to extract a word-emotion lexicon automati- cally from an emotion labelled corpus of tweets. Our results confirm that the fea- tures derived from these lexicons outper- form the standard Bag-of-words features when applied to an emotion classification task. Furthermore, a comparative analysis with both manually crafted lexicons and a state-of-the-art lexicon generated using Point-Wise Mutual Information, show that the lexicons ge...