Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
A rule-based policy language for selective trust propagation in social networks
Databases and Social Networks
D2SNet: Dynamics of diffusion and dynamic human behaviour in social networks
Computers in Human Behavior
Spatio-temporal and events based analysis of topic popularity in twitter
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
StaticGreedy: solving the scalability-accuracy dilemma in influence maximization
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
An Efficient Multi-Path Self-Organizing Strategy in Internet of Things
Wireless Personal Communications: An International Journal
Towards combating rumors in social networks: Models and metrics
Intelligent Data Analysis - Dynamic Networks and Knowledge Discovery
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In this paper we study and evaluate rumor-like methods for combating the spread of rumors on a social network. We model rumor spread as a diffusion process on a network and suggest the use of an "anti-rumor" process similar to the rumor process. We study two natural models by which these anti-rumors may arise. The main metrics we study are the belief time, i.e., the duration for which a person believes the rumor to be true and point of decline, i.e., point after which anti-rumor process dominates the rumor process. We evaluate our methods by simulating rumor spread and anti-rumor spread on a data set derived from the social networking site Twitter and on a synthetic network generated according to the Watts and Strogatz model. We find that the lifetime of a rumor increases if the delay in detecting it increases, and the relationship is at least linear. Further our findings show that coupling the detection and anti-rumor strategy by embedding agents in the network, we call them beacons, is an effective means of fighting the spread of rumor, even if these beacons do not share information.