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Community-based greedy algorithm for mining top-K influential nodes in mobile social networks
Abstract
With the proliferation of mobile devices and wireless technologies, mobile social network systems are increasingly available. A mobile social network plays an essential role as the spread of information and influence in the form of "word-of-mouth". It is a fundamental issue to find a subset of influential individuals in a mobile social network such that targeting them initially (e.g. to adopt a new product) will maximize the spread of the influence (further adoptions of the new product). The problem of finding the most influential nodes is unfortunately NP-hard. It has been shown that a Greedy algorithm with provable approximation guarantees can give good approximation; However, it is computationally expensive, if not prohibitive, to run the greedy algorithm on a large mobile network.
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Finding and evaluating community structure in networks
Newman, M. E. J., & Girvan, M. (2004) · Physical Review E · doi:10.1103/physreve.69.026113 · Cited by 13,931
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Li, Y., Fan, J., Wang, Y., & Tan, K.-L. (2018) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2018.2807843 · Cited by 659
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Chen, W., Collins, A., Cummings, R., Ke, T., Liu, Z., Rincon, D., Sun, X., Wang, Y., Wei, W., & Yuan, Y. (2011) · Proceedings of the 2011 SIAM International Conference on Data Mining · doi:10.1137/1.9781611972818.33 · Cited by 352
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Metadata
- Authors
- Wang, Y., Cong, G., Song, G., & Xie, K.
- Venue
- Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
- Publisher
- ACM
- Published
- 2010-07-25
- Pages
- 1039-1048
- OpenAlex
- W2158478952
- Cited by
- 541
- References
- 1
- FWCI
- 18.04
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Wang, Y., Cong, G., Song, G., & Xie, K. (2010). Community-based greedy algorithm for mining top-K influential nodes in mobile social networks. Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining. https://doi.org/10.1145/1835804.1835935
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