Serendio: Simple and Practical lexicon based approach to Sentiment Analysis
Prabu palanisamy, Vineet Yadav, Harsha Elchuri · 2013
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 taxonomy. The Serendio taxonomy consists of positive, negative, negation, stop words and phrases. A typical tweet contains word variations, emoticons, hashtags etc. We use preprocessing steps such as stemming, emoticon detection and normalization, exaggerated word shortening and hashtag detection. After the preprocessing, the lexicon-based system classifies 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. 1