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2019 | OriginalPaper | Chapter

Parallel Multicast Information Propagation Based on Social Influence

Authors : Yuqi Fan, Liming Wang, Lei Shi, Dingzhu Du

Published in: Wireless Algorithms, Systems, and Applications

Publisher: Springer International Publishing

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Abstract

Most research on information propagation in social networks does not consider how to find information dissemination paths from the information source node to a set of influential nodes. In this paper, we introduce a multicast information propagation model which disseminates information from the information source node to a set of designated influential nodes in social networks, and formulate the problem with the objective to maximize the social influence on the information propagation paths. We then propose a Parallel Multicast information Propagation algorithm (PMP), which concurrently constructs a subgraph for each influential node, joins all the subgraphs into a merge graph, and finds the information propagation paths with the maximum social influence in the merge graph. The simulation results demonstrate that the proposed algorithm can achieve competitive performance in terms of the social influence on the information propagation paths.

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Literature
1.
Peng, S., Zhou, Y., Cao, L., et al.: Influence analysis in social networks: a survey. J. Netw. Comput. Appl. 106(2018), 17–32 (2018)
2.
Kempe, D., Kleinberg, J., Tardos, E.: Maximizing the spread of influence through a social network. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Washington, D.C., pp. 137–146 (2003)
3.
He, Z., Cai, Z., Wang, X.: Modeling propagation dynamics and developing optimized countermeasures for rumor spreading in online social networks. In: 2015 IEEE 35th International Conference on Distributed Computing Systems, Columbus, USA, pp. 205–214 (2015)
4.
He, Z., Cai, Z., Yu, J., et al.: Cost-efficient strategies for restraining rumor spreading in mobile social networks. IEEE Trans. Veh. Technol. 66(3), 2789–2800 (2017)
5.
Wang, Z., Shinkuma, R., Takahashi, T.: Dynamic social influence modeling from perspective of gray-scale mixing process. In: 9th International Conference on Mobile Computing and Ubiquitous Network, Hakodate, Japan, pp. 1–6 (2015)
6.
Zhu, Y., Wu, W., Bi, Y., et al.: Better approximation algorithms for influence maximization in online social networks. J. Comb. Optim. 30(1), 97–108 (2015)
7.
Li, J., Cai, Z., Yan, M., Li, Y.: Using crowdsourced data in location-based social networks to explore influence maximization. In: The 35th Annual IEEE International Conference on Computer Communications, San Francisco, USA, pp. 1–9 (2016)
8.
Tong, G., Wu, W., Tang, S., et al.: Adaptive influence maximization in dynamic social networks. IEEE/ACM Trans. Netw. 25(1), 112–125 (2017)
9.
Dinh, T., Nguyen, H., Ghosh, P., et al.: Social influence spectrum with guarantees: computing more in less time. In: International Conference on Computational Social Networks, Beijing, China, pp. 84–103 (2015)
10.
Leskovec, J., Sosic, R.: SNAP: a general-purpose network analysis and graph-mining library. ACM Trans. Intell. Syst. Technol. 8(1), 1 (2016)
Metadata
Title
Parallel Multicast Information Propagation Based on Social Influence
Authors
Yuqi Fan
Liming Wang
Lei Shi
Dingzhu Du
Copyright Year
2019
Book
Wireless Algorithms, Systems, and Applications

Print ISBN: 978-3-030-23596-3

Electronic ISBN: 978-3-030-23597-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-23597-0_46

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