Sentiment Analysis of Product Review
Keywords:
Sentiment Analysis, Naive Bayes, Mining, Support Vector Machine, Supervised approach, Unsupervised approach, Polarity, SemanticAbstract
Sentiment analysis is defined as the process of mining of data, view, review or sentence to predict the emotion of the sentence through natural language processing (NLP). The sentiment analysis involves classification of text into three phase "Positive", "Negative" or "Neutral". It analyses the data and labels the 'better' and 'worse' sentiment as positive and negative respectively. Using social media, e-commerce website, movies reviews such as Facebook, twitter, Amazon, Flipkart etc. user share their views, feelings in a convenient way. To analysis of such huge data automatically, the field of sentiment analysis has turn up. The main aim of sentiment analysis is to identifying polarity of the data in the Web and classifying them. Therefore, to find polarity or sentiment of, user or customer there is a demand for automated data analysis techniques. In this paper, a detailed survey of different techniques or approach is used in sentiment analysis and a new technique which is proposed in this paper.
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