STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Telecommunication, Switching Systems and Networks

Reducing Of Misinformation InflunceIn Online Social Network Using Heuristic Greedy Algorithm

  1. K Sangamma
  2. K Nagaraju
  3. L Venu Madhav

Abstract

Now a day we use social media to communicate and share the information throughout the world. Many of us depend on this social media now a days everything is available here, once we access the media, we lots of information about our search, there is chances of have misinformation also. The authenticity of information content is weakened, and all kinds of misinformation depend on social media to spread rapidly. Network space governance and providing a trusted network platform are of critical significance. In this paper, we analyze a problem called Reducing of Misinformation Influence (RMI) problem that stops a node set from the network. That is to say, the RMI problem is to selects the nodes from social network and blocks the nodes, so that the TAMIN is the smallest. We prove that the objective function is neither sub modular nor super modular and propose a heuristic greedy algorithm (HGA) to select top K nodes for removal

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