A Survey on Sentiment Classification and Analysis using Data Mining

Ashish Shukla, Shweta Shukla


Sentiment analysis is a type of natural language processing that tracks the opinion and mood of the public about the specific product. The volume of information in digital form increases day-by-day as people express their sentiments, also called opinions everywhere mostly on internet as the people now days are much dependent on internet. So the requirement of user opinions analysis is gaining importance day by day. Blogs, micro blogs, review sites, twitter, and other social networks are the most common platforms that are used by people and organizations for posting their views. Researchers has done very immense effort in the field of sentiment analysis and also new opportunities and challenges still arise so even now it is very active and dynamic research area in the field of natural language processing. It is also widely investigated in text mining, data mining and web mining. This paper attempts to evaluate the several techniques used for sentiment analysis. The goal of this survey is to give an in-depth introduction to this fascinating problem and to present a comprehensive study of all important research using data mining and the latest developments in the field.

Keywords: Opinion Mining, NLP, Sentiment Analysis, Information Retrieval, Naïve Bayes Algorithm

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DOI: https://doi.org/10.26483/ijarcs.v6i7.2565


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