The Impact of Z_score on Twitter Sentiment Analysis
نویسندگان
چکیده
Twitter has become more and more an important resource of user-generated data. Sentiment Analysis in Twitter is interesting for many applications and objectives. In this paper, we propose to exploit some features which can be useful for this task; the main contribution is the use of Z-scores as features for sentiment classification in addition to pre-polarity and POS tags features. Our experiments have been evaluated using the test data provided by SemEval 2013 and 2014. The evaluation demonstrates that Z_scores features can significantly improve the prediction performance.
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