Lexicon Based Sentiment Analysis of Twitter Data

Abstract

Abstract: Sentiment Analysis of twitter data is an active area of Natural Language Processing research. This study explores a unsupervised lexicon based approach to calculate polarity of tweets fro a publicly available twitter corpus. Along with lexicon based search of sentiment bearing words, several rule based methods are used to get the final polarity count of tweets. This study takes into account effect of negation, capitalization, multiple punctuation, slang, and degree modifier