DRIMUX: Dynamic Rumor Influence Minimization with User Experience in Social Networks (Oct-2017)
The main aim of this project is to identify the real rumor person and eliminate fake post and rumor person in the social Network.
In this proposed method we propose a novel source identification method to overcome the challenges. To represent a time-varying social network, we reduce it to a sequence of static networks, each aggregating all edges and nodes present in a time-integrating window. This is the case, for instance, of rumors spreading in Social networks, for which the fine-grained temporal resolution is not available, In each integrating window, if users did not activate the Mobile data pack on their devices (i.e.,offline), they would not receive or spread the rumors. The detective routine in criminology, a small set of suspects will be identified by adopting a reverse dissemination process to narrow down the scale of the source. The reverse dissemination process distributes copies of rumors reversely from the users whose states have been determined based on various observations upon the networks. The ones who can simultaneously receive all copies of rumors from the infected users are supposed to be the suspects of the real sources.