A Survey: Prediction of Rating Based on Social Sentiment from Textual Reviews

Arshiya Begum, Ruksar Fatima


In recent years, shopping online is becoming moreand more popular. When its needed to decide whether to purchase a product or not on-line, the opinions of others become important. Product or service retrieval from the huge data becomes very trouble, so users review and ratings are considered as a major point for recommendation and filtering. But, the user’s reviews are very high and this need a lot of time to take decision from the reviews. So, there is a need to summarize the reviews with finding sentiment analysis. This paper presents a survey on various Sentiment Analysis and mining techniques with different applications. From the comparative study, the new and optimal method can be detected and used for web app recommendation with Rating Prediction from huge set of text reviews.

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