Paper: AVAYA: Sentiment Analysis on Twitter with Self-Training and Polarity Lexicon Expansion

ACL ID S13-2055
Title AVAYA: Sentiment Analysis on Twitter with Self-Training and Polarity Lexicon Expansion
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes the systems submitted by Avaya Labs (AVAYA) to SemEval-2013 Task 2 - Sentiment Analysis in Twitter. For the constrained conditions of both the message polarity classification and contextual polarity disambiguation subtasks, our approach cen- ters on training high-dimensional, linear clas- sifiers with a combination of lexical and syn- tactic features. The constrained message po- larity model is then used to tag nearly half a million unlabeled tweets. These automati- cally labeled data are used for two purposes: 1) to discover prior polarities of words and 2) to provide additional training examples for self-training. Our systems performed compet- itively, placing in the top five for all subtasks and data conditions. More importantly, these results show that expanding th...