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User Review Analysis using Multi-Modal Summarization Algorithm


Mrs. Deepti Nirwal , P.E.S. Modern College Of Engineering; Kajal Mirje, P.E.S. Modern College Of Engineering; Tejashree Ore, P.E.S. Modern College Of Engineering; Mayuri Patil, P.E.S. Modern College Of Engineering; Unnati Munot, P.E.S. Modern College Of Engineering


Sentiment Analysis, Sentiment Score


Many e-commerce websites enables their customers to write product reviews or give ratings to the product based on the opinion. These reviews and rating helps the company to understand their standing in the market and also helps the fellow customers to form an opinion in purchase of a product. Due to this reason of profit or fame, many target products are promoted or demoted in the form of spam. This may contains fake reviews or malicious opinions. We can make an attempt to identify the spam and fake reviews and filter out such reviews which contains curse and vulgar words by using sentiment analysis. In this we are taking Twitter data of a particular product which will be pre-processed and filtered. After that on the filtered data we are going to perform sentiment analysis which will provide the score-tag to the particular tweet. We are going to summarize the similar tweets using multi-modal summarization algorithm. In the final result based on the score-tag provided and summarization we will graphically show the analyses of the product and how customer has reviewed (negative, positive and neutral) which adds to its popularity or demotion.

Other Details

Paper ID: IJSRDV7I20687
Published in: Volume : 7, Issue : 2
Publication Date: 01/05/2019
Page(s): 772-774

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