Objective: To analysis different techniques and approaches for sentiment analysis to know the user opinion about a product or event or service that helps to improve an organization.
Findings: In an emerging network every company wants to know users opinion about their product or service. Each and every user has different views about the product or service and their views are expressed through reviews. The analysis of such opinion from different users plays an important role in the growth of a company. The opinions are expressed through reviews in the natural language. Sentiment analysis is a process used to identify emotions, opinions and evaluations and it also predict the orientation of sentiment whether the sentiment is positive, neutral or negative opinion based on the words or sentences expressed in the reviews. Sentiment analysis is otherwise called as opinion mining. In this paper various techniques and approaches for sentiment analysis are analysed and finally compared their effectiveness through parameters like accuracy, precision, recall and F-measure values.
Results: In this paper various techniques for sentiment analysis techniques are compared through parameters to prove unsupervised approach at aspect level for sentiment analysis is better than other techniques.
Application/Improvements: The finding of this work shows that unsupervised approach at aspect level for sentiment analysis is better than other techniques.
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