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Scientific Paper Reviews Identification by Sentiment Analysis in Data Mining

Anand Singh, Sitaram Patel, Megha Kamble

Abstract


Abstract

Sentiment analysis (SA) is one of the rapidly growing fields of research in computer science and makes it difficult to track all activities in the area. Analyzes of thoughts and/or perceptions are used for automating subjective information identification such as opinions, attitudes, emotions, and feelings. Hundreds of thousands are concerned about science and take a long time to select appropriate papers for their research. These opinions are numerous and SA can be used to mine the general sentiment or opinion polarity of all of them. It is nearly difficult to manually evaluate such a vast number of comments. The automatic solution of a computer, therefore, has a significant role to play in resolving this serious issue. The biggest problem in perception analytics and opinion mining (OM) is the recognition of emotions in these texts. In this paper we survey on opinion mining concerning their different techniques, tools applied, and also describe the overview of sentiment analysis regarding levels, approaches, challenges, and benefits as well as techniques of data mining. This survey is also done to study the opinion mining and sentiment analysis used to scientific paper review.

 

Keywords: Data mining, opinion mining, sentiment analysis, scientific paper reviews, data mining techniques


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