Abstract:
With the prevalence of social media as a medium of communication in today’s society, countering the spread of fake news on the network has become an important area of study. In this work, we study the notion of competing campaigns in a social network and address the problem of influence limitation where a ”bad” campaign starts propagating from a certain node in the network and we have to propagate a limiting campaign to counteract the effect of misinformation for a particular set of nodes called ”sensitive nodes”. The problem can be summarized as identifying a subset of individuals that need to be convinced to adopt the competing (or ”good”) campaign so as to minimize the number of sensitive nodes that adopt the ”bad” campaign at the end of both propagation processes. We show that the problem of finding the minimum number of nodes is NP-hard and experimentally compare the performance of various heuristics with our proposed prediction algorithm.
