Paper: TeamX: A Sentiment Analyzer with Enhanced Lexicon Mapping and Weighting Scheme for Unbalanced Data

ACL ID S14-2111
Title TeamX: A Sentiment Analyzer with Enhanced Lexicon Mapping and Weighting Scheme for Unbalanced Data
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2014
Authors

This paper describes the system that has been used by TeamX in SemEval-2014 Task 9 Subtask B. The system is a senti- ment analyzer based on a supervised text categorization approach designed with fol- lowing two concepts. Firstly, since lex- icon features were shown to be effective in SemEval-2013 Task 2, various lexicons and pre-processors for them are introduced to enhance lexical information. Secondly, since a distribution of sentiment on tweets is known to be unbalanced, an weighting scheme is introduced to bias an output of a machine learner. For the test run, the sys- tem was tuned towards Twitter texts and successfully achieved high scoring results on Twitter data, average F 1 70.96 on Twit- ter2014 and average F 1 56.50 on Twit- ter2014Sarcasm.