شناسایی منبع شایعه در شبکه های اجتماعی با توپولوژی متغیر با زمان Rumor Source Identification in Social Networks with Time-Varying Topology

1 INTRODUCTION RUMORS spreading in social networks have long been a critical threat to our society. A recent incident of rumors “Obama was injured in two explosions of White House” led to 10 billion USD losses in a few hours. This demonstrates that a single rumor can cause great damage to business and life [1]. Nowadays, with the development of mobile devices and wireless techniques, the temporal nature of social networks (time-varying social networks) has a deep influence on dynamical information spreading processes occurring on top of them [2]. The ubiquity and easy access of social networks not only promote the efficiency of information sharing but also dramatically accelerate the speed of rumor spreading [3]. Rumors combine the characteristics of the “word-of-mouth” spreading scheme with the dynamic connections between individuals in time-varying social networks [4]. For either forensic or defensive purposes, it has always been a significant work to identify the source of rumors in time-varying social networks [5]. However, the existing techniques generally require firm connections between individuals (i.e., static networks) so that administrators can trace back along the determined connections to reach the spreading sources. For example, many methods rely on identifying spanning trees in networks [6]–[8], then the roots of the spanning trees are regarded as the rumor sources. The firm connections between users are the premise of constructing spanning trees in these methods. Some other methods detect rumor sources by measuring node centralities [9], [10]. The individual who has the maximum centrality value is considered as the rumor source. All of these centrality measures are based on static networks. Time-varying social networks, where users and interactions evolve over time, have led to great challenges to the traditional rumor source identification techniques.