Author : Ms. Deepika V. Vachane and Prof. Gopal D. Upadhye

Generally the people trust on product on the basis of that product reviews and rating. People can take off a survey give a chance to spammers to compose spam surveys about goods and services for various benefits. Recognizing these fake reviewers and the spam content is a big debated issue of research and despite of the fact that an various number research has been done already. Up till now the procedures set hardly differentiate spam reviews, and no one show the significance of every property type. In this investigation, a structure, named NetSpam, which uses spam highlights for demonstrating review data sets as heterogeneous information networks to design spam identification method into a group of issue in this networks. Utilizing the significance of spam features help us to acquire good outcomes regarding different metrics on review data sets. The contribution work is when user search query it will display all n-no of products as well as recommendation of the product.

Keywords: Social Media, Social Network, Spammer, Spam Review, Fake Review, Heterogeneous Information Networks.