Result Based Spam Detection Technologies for Heterogeneous Information Networks
Author Name : Ms. Karad Vandana A, Prof. Rokade M. D
ABSTRACT Everyday’s, a important part of every person’s trusts on information in social media like comments, opinions and feedback of a item. The person that anyone can taken a survey give a golden chance to spammers to compose spam surveys regarding products and services for many interests. Analysing these spammers and the spam content is a wildly debated issue of research and in spite of the fact that an impressive number of studies have been completed as of this end, now the far procedures set still scarcely differentiate spammer reviews, and nobody can demonstrate and experimental the significance of each and every extracted feature type of misleading data on the social media networks. In this paper, I propose a structure, name as the Net Spammer, it uses spam foreground for demonstrating and calculating review, rating historical datasets as heterogeneous information networks to develop network spam detection technologies into a classification problem in such networks. The result output demonstrate that Net Spam results the existing techniques and proposed techniques consist four types of methods of features; including review-behavioral, user-behavioral, review linguistic, user-linguistic.