Paper: Is Twitter A Better Corpus for Measuring Sentiment Similarity?

ACL ID D13-1091
Title Is Twitter A Better Corpus for Measuring Sentiment Similarity?
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

Extensive experiments have validated the ef- fectiveness of the corpus-based method for classifying the word?s sentiment polarity. However, no work is done for comparing d- ifferent corpora in the polarity classification task. Nowadays, Twitter has aggregated huge amount of data that are full of people?s senti- ments. In this paper, we empirically evaluate the performance of different corpora in sen- timent similarity measurement, which is the fundamental task for word polarity classifica- tion. Experiment results show that the Twitter data can achieve a much better performance than the Google, Web1T and Wikipedia based methods.