Spammers detection based on reviewers’ behaviors under belief function theory

Abstract

Nowadays, we note the dominance of the online reviews which become an essential factor in customers’ decision to purchase a product or service. Driven by the immense financial profits from reviews, some corrupt individuals or organizations deliberately post fake reviews to promote their products or to demote their competitors’ products, trying to mislead or influence customers. Therefore, it is crucial to spot these spammers in order to detect the deceptive reviews, to protect companies from this harmful action and to ensure the readers confidence. In this way, we propose a novel approach able to detect spammers and to accord a spamicity degree to each reviewer relying on some spammers indicators while handling the uncertainty in the different inputs through the strength of the belief function theory. Tests are conducted on a real database from Tripadvisor to evaluate our method performance.