Rumour Control Model to Prevent Falsehood Propagation in Social Media

Social media has rapidly evolved as a standard of communication that potentially facilitates information sharing and publishing across virtual communities. This online networked community is often victimized of rumours and fake content being diffused in streams of social dialogues. Propagation of rumours is considered as a devastating social phenomena, which results in fatal consequences over social media. With the advent of online social networks, malicious users have started using these platforms for spreading rumours. Most research focuses on analyzing the post impacts of the rumours spread. However, the underlying idea of our research lies in the fact of detecting possibilities of preventing the falsehood propagation, thereby controlling the spread of rumours in the network. This is achieved by designing a directed network graph of the users on the basis of the followers they have. The edges of the graph were assigned weights which is the probability of rumours likely to be diffused by the associated nodes provided that its follower or followee has already been infected. The performance of our proposed Rumour Control Model (RCM) is verified for different parameters as well as with existing Independent Cascade (IC) diffusion model for simulating the spread of rumour.