Improved Feature Extraction and Classification - Sentiment Analysis

Sentiment analysis is becoming a popular area of research and social media analysis, especially around user reviews and tweets. It is a special case of text mining generally focused on identifying opinion polarity, People are usually interested to seek positive and negative opinions containing likes and dislikes, shared by users. Therefore reviews or product features have got significant role in sentiment analysis. In addition to sufficient work being performed in text analytics, feature extraction in sentiment analysis is now becoming an active area of research. Feature based sentiment analysis include feature extraction, sentiment classification and finally the sentiment evaluation. In this paper, explored the machine learning classification approaches with different feature selection schemes to obtain a sentiment analysis model for the movie review dataset and the results obtained are compared to identify the best possible approach.