A NAÏVE BAYES REPUTATION GENERATING MODEL BASED ON SENTIMENT ANALYSIS AND OPINION FUSION

Authors:

Arpita Gupta,Saloni Priyani,Ramadoss Balakrishnan,

DOI NO:

https://doi.org/10.26782/jmcms.spl.6/2020.01.00007

Keywords:

Reputation Generation,Naïve Bayes,Sentiment Analysis,Opinion Mining,Weighted Arithmetic Mean,

Abstract

In recent times, reviewing the product on the seller website is very convenient and helpful for other users. The seller websites have provided a userfriendly platform to express their opinion or review of a product without any biases. These reviews help other users make better decisions, so the process of reputation generation is of great relevance at the current time. Reputation is the score of credibility and reliability, which plays a vital role as having a poor reputation could affect the product market value. So, generating an accurate reputation is critical. We have proposed a Naïve Bayes unigram and bigram-based model which performs opinion mining and sentiment analysis and generates reputation using Weighted Arithmetic Mean value on the movie dataset. The results have shown improvement with respect to the existing models.

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