Paper: Serendio: Simple and Practical lexicon based approach to Sentiment Analysis

ACL ID S13-2091
Title Serendio: Simple and Practical lexicon based approach to Sentiment Analysis
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes the system developed by the Serendio team for the SemEval-2013 Task 2 competition (Task A). We use a lexicon based approach for discovering sentiments. Our lexicon is built from the Serendio tax- onomy. The Serendio taxonomy consists of positive, negative, negation, stop words and phrases. A typical tweet contains word varia- tions, emoticons, hashtags etc. We use prepro- cessing steps such as stemming, emoticon de- tection and normalization, exaggerated word shortening and hashtag detection. After the preprocessing, the lexicon-based system clas- sifies the tweets as positive or negative based on the contextual sentiment orientation of the words. Our system yields an F-score of 0.8004 on the test dataset.