Predictive Analytics for Online Social Networks

Abstract

A number of information-sharing platforms have sprung up on the Internet, such as the Web. The Web is focused on content, whereas Online Social Networks (OSNs) are oriented around the users. OSNs handle social relations between users, locate content and knowledge shared by other users, and connect users with similar interests. A revolution in social interaction has occurred in current decades due to the popular OSNs such as Facebook, Orkut, Twitter, and LinkedIn. It has become an essential aspect of the information society to study OSNs, a multidisciplinary research area. The survey of OSNs structures covers methods for analyzing the structures, observing various patterns in these structures, identifying influential users, etc. The data generated in OSNs raises tremendous challenges and opportunities from the perspective of predictive analytics. Predictive analytics is the process of analyzing the data to make event or behavior predictions. The predictive analytics framework is for building and deploying predictive models.