Natural Language Processing for Sentiment Analysis: An Exploratory Analysis on Tweets

In this paper, we present our preliminary experiments on tweets sentiment analysis. This experiment is designed to extract sentiment based on subjects that exist in tweets. It detects the sentiment that refers to the specific subject using Natural Language Processing techniques. To classify sentiment, our experiment consists of three main steps, which are subjectivity classification, semantic association, and polarity classification. The experiment utilizes sentiment lexicons by defining the grammatical relationship between sentiment lexicons and subject. Experimental results show that the proposed system is working better than current text sentiment analysis tools, as the structure of tweets is not same as regular text.