The Community for Technology Leaders
2013 IEEE 33rd International Conference on Distributed Computing Systems (2013)
Philadelphia, PA USA
July 8, 2013 to July 11, 2013
ISSN: 1063-6927
pp: 540-549
Lidan Fan , Dept. of Comput. Sci., Univ. of Texas at Dallas Dallas, Dallas, TX, USA
Zaixin Lu , Dept. of Comput. Sci., Univ. of Texas at Dallas Dallas, Dallas, TX, USA
Weili Wu , Dept. of Comput. Sci., Univ. of Texas at Dallas Dallas, Dallas, TX, USA
Bhavani Thuraisingham , Dept. of Comput. Sci., Univ. of Texas at Dallas Dallas, Dallas, TX, USA
Huan Ma , Sch. of Inf., Renmin Univ. of China, Beijing, China
Yuanjun Bi , Dept. of Comput. Sci., Univ. of Texas at Dallas Dallas, Dallas, TX, USA
ABSTRACT
In many real-world scenarios, social network serves as a platform for information diffusion, alongside with positive information (truth) dissemination, negative information (rumor) also spread among the public. To make the social network as a reliable medium, it is necessary to have strategies to control rumor diffusion. In this article, we address the Least Cost Rumor Blocking (LCRB) problem where rumors originate from a community Cr in the network and a notion of protectors are used to limit the bad influence of rumors. The problem can be summarized as identifying a minimal subset of individuals as initial protectors to minimize the number of people infected in neighbor communities of Cr at the end of both diffusion processes. Observing the community structure property, we pay attention to a kind of vertex set, called bridge end set, in which each node has at least one direct in-neighbor in Cr and is reachable from rumors. Under the OOAO model, we study LCRB-P problem, in which α (0 <; α <; 1) fraction of bridge ends are required to be protected. We prove that the objective function of this problem is submodular and a greedy algorithm is adopted to derive a (1-1/e)-approximation. Furthermore, we study LCRB-D problem over the DOAA model, in which all the bridge ends are required to be protected, we prove that there is no polynomial time o(ln n)-approximation for the LCRB-D problem unless P = NP, and propose a Set Cover Based Greedy (SCBG) algorithm which achieves a O(ln n)-approximation ratio. Finally, to evaluate the efficiency and effectiveness of our algorithm, we conduct extensive comparison simulations in three real-world datasets, and the results show that our algorithm outperforms other heuristics.
INDEX TERMS
Communities, Bridges, Integrated circuit modeling, Approximation algorithms, Approximation methods, Social network services, Greedy algorithms,social networks, least cost rumor blocking, opportunistic One-Activate-One model, deterministic One-Activate-Many model, approximation algorithm
CITATION
Lidan Fan, Zaixin Lu, Weili Wu, Bhavani Thuraisingham, Huan Ma, Yuanjun Bi, "Least Cost Rumor Blocking in Social Networks", 2013 IEEE 33rd International Conference on Distributed Computing Systems, vol. 00, no. , pp. 540-549, 2013, doi:10.1109/ICDCS.2013.34
193 ms
(Ver 3.3 (11022016))