Misinformation Blocking Problem in Virtual and Real Interconversion Social Networks

Abstract

With the in-depth development of intelligent media technology, online and offline fusion, reality and virtual entanglement, information content generalization, the boundary between positive and negative information is blurred, all kinds of misinformation in the social network fission spread, and cyberspace governance has become a global consensus. In this article, we comprehensively consider the spread of misinformation in location-based interpersonal social network and online social network, and systematically tackle the novel problem of minimizing the influence of misinformation under individual protection strategies. We first analyze the complexity and modularity of the problem. Then, we leverage the Lovász extension to devise a nonsubmodular set function continuity approximate convex relaxation method, and develop an approximate projected subgradient procedure to obtain a solution with a factor approximate guarantee. Finally, experiments on three assembled real-world datasets demonstrate the effectiveness and feasibility of our designed method and developed the algorithm.