Introduction of Opinion Mining and Sentiment Analysis Research

Authors

  • Varma Kajal S Department of Information Technology, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Raval Jyoti A Department of Information Technology, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Mr.Romil Patel Assistant Professor, Department of IT, Sigma Institute of Engineering, Vadodara, Gujarat, India.

Keywords:

Opinion mining and sentiment analysis, web mining, system flow, naïve Bayesian algorithm, Applications, Techniques

Abstract

In our project important parts are opinion mining, spam detection, company rating and data
cleaning. In data cleaning we had clean the data which are unwanted and also count the how many data are
removed. Spam detection is based on the data cleaning process. Spam detection is identify in data which are
spam or non-spam data based on same user, same ip address, same product id and same time. Opinion mining
is based on the Non-spam data. In opinion mining process we can find the positive reviews, negative reviews
and neutral reviews. For opinion mining we are used naive Bayesian algorithm. All data are stored in dataset.
Company rating is also based on data cleaning process. In company rating we can find the highest rated
company.

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Published

2016-04-25

How to Cite

Varma Kajal S, Raval Jyoti A, & Mr.Romil Patel. (2016). Introduction of Opinion Mining and Sentiment Analysis Research. International Journal of Advance Research in Engineering, Science & Technology, 3(4), 223–230. Retrieved from https://ijarest.org/index.php/ijarest/article/view/536

Issue

Vol. 3 No. 4 (2016): Volume: 03, Issue: 04 - April, 2016.

Section

Articles