Tweet Analyzer: Identifying Interesting Tweets Based on the Polarity of Tweets

摘要

Sentiment analysis is the process of finding the opinions present in the textual content. This paper proposes a tweet analyzer to perform sentiment analysis on twitter data. The work mainly involves the sentiment analysis process using various trained machine learning classifiers applied on large collection of tweets. The classifiers have been trained using maximum number of polarity oriented words for effectively classifying the tweets. The trained classifiers at sentence level outperformed the keyword based classification method. The classified tweets are further analyzed for identifying top N tweets. The experimental results show that the sentiment analyzer system predicted polarities of tweet and effectively identified top N tweets.