Paper Details

In routine day to day life, customer opinions about certain things play a crucial role. Opinions of otherindividuals are used for consideration in our decision making process. Many web users use platforms such as blogs,review sites, social networking sites to post/give their opinions regarding many products. Customer or individual’sopinion or view regarding products, support and services for organizations has always been a keen interest and researchmatter for each organization. The crucial part is to analyze good amount of social data present on the webautomatically with the rapid growth and expansion of e-commerce and online shopping. This leads to create methodswhich classify them automatically. Opinion mining is sometimes called as Sentiment Classification. SentimentClassification is defined as mining and analyzing of views, reviews, emotions and opinions automatically from text, bigdata and speech by means of various methodologies. In this thesis, negation handling method with POS tagging todecrease the negation words is used and then we are going to see how Frequent Pattern mining algorithm can be usedfor mining reviews from online reviews which are posted by customers. Creating an effective approach for analyzingopinions which implies judgments of different consumer products is our main aim.

Nilesh Vaghela, “Decision Making Using Opinion Mining With Negation Handling Considering Customer Evaluation”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 2, pp. 529-532, February 2018.