Credibility assessment of public pages over Facebook

Abstract

With the growing use of online social media and presence of users on many such platforms, their interaction with social networks is huge. They are free to spread wrong information without any accuracy, integrity and authenticity checkpoints masquerading as legitimate content. All these wrong, unrelated, unwanted, manipulated information are distributed for some hidden reasons. Even, their distribution network is not limited to one social media platform. Sometimes, they use the social network as a market place either for advertising, promotion of particular website, product and an application. But these advertisements do not provide any incentive to Facebook as this content is just spam, irrelevant for Facebook. Dissemination of unwanted, unrelated information has become a huge problem not only on blog, discussion forum but also on online social network like Facebook. Due to lack of marking over content posted, this information become online and reader has no barometer to check either the credibility of commenter or poster or the credibility of facts. To address these issues, we have derived an equation to weigh the credibility of public pages and applied machine learning algorithms (MLA) over collected data to validate our prediction.