WEB SENTIMENT ANALYSIS FOR SCORING POSITIVE OR NEGATIVE ASPECT IN SOCIAL NETWORKING SITES

Miss Ravina D. Shukla Shukla
Department of computer science and engineering SSGMCE, Shegaon, India. , IN

Prof.C.M. Mankar Mankar
Department of computer science and engineering SSGMCE, Shegaon, India. , IN

Abstract

In recent years, we all are witnessed a flourish of review websites. It represents a great opportunity to share our thoughts for various products we purchase. However, we face the information overloading problem. How to examine valuable information from reviews to understand a user’s preferences and make an accurate recommendation is crucial. Traditional recommended systems (RS) consider some factors, such as user’s purchase records, product category, and geographic location. In this work, we propose a sentiment-based rating prediction method (RPS) to improve prediction accuracy in recommended systems. First, we propose web sentimental on social
user measurement approach and calculate each user’s sentiment on items/products. Second, we consider not only a user’s own sentimental attributes but also take interpersonal sentimental influence into consideration. Then, consider posts reputation, which can be inferred by the sentimental distributions of a user set that reflect customers’ comprehensive comments. At last, we use three factors-user sentiment similarity, interpersonal sentimental influence, and item’s reputation similarity into our recommended system to make an accurate rating prediction. and conduct a performance evaluation of the the sentimental factors on a real-world data set collected from Yelp. Our experimental results show the sentiment can well characterize user preferences, which help to improve the recommendation performance.

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