期刊
ACM TRANSACTIONS ON KNOWLEDGE DISCOVERY FROM DATA
卷 3, 期 2, 页码 -出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/1514888.1514892
关键词
Contamination diffusion; link analysis; social networks
资金
- Asian Office of Aerospace Research and Development, Air Force Office of Scientific Research, U.S. Air Force Research Laboratory [AOARD-08-4027]
- JSPS [20500147]
- Grants-in-Aid for Scientific Research [20500147] Funding Source: KAKEN
We address the problem of minimizing the propagation of undesirable things, such as computer viruses or malicious rumors, by blocking a limited number of links in a network, which is converse to the influence maximization problem in which the most influential nodes for information diffusion is searched in a social network. This minimization problem is more fundamental than the problem of preventing the spread of contamination by removing nodes in a network. We introduce two definitions for the contamination degree of a network, accordingly define two contamination minimization problems, and propose methods for efficiently finding good approximate solutions to these problems on the basis of a naturally greedy strategy. Using large social networks, we experimentally demonstrate that the proposed methods outperform conventional link-removal methods. We also show that unlike the case of blocking a limited number of nodes, the strategy of removing nodes with high out-degrees is not necessarily effective for these problems.
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