Abstract
There exist two or more competing products in viral marketing, and the companies can exploit the social interactions of users to propagate the awareness of products. In this paper, we focus on selecting seeds for maximizing the competitive influence spread in social networks. First, we establish the possible graphs based on the propagation probability of edges, and then we use the competitive influence spread model (CISM) to model the competitive spread under the possible graph. Further, we consider the objective function of selecting k seeds of one product under the CISM when the seeds of another product have been known, which is monotone and submodular, and thus we use the CELF (cost-effective lazy forward) algorithm to accelerate the greedy algorithm that can approximate the optimal with 1 − 1/e. Experimental results verify the feasibility and effectiveness of our method.
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Acknowledgement
This paper was supported by the National Natural Science Foundation of China (61472345, 61562091), the Natural Science Foundation of Yunnan Province (2014FA023, 2013FB010), the Program for Innovative Research Team in Yunnan University (XT412011), the Program for Excellent Young Talents of Yunnan University (XT412003), Yunnan Provincial Foundation for Leaders of Disciplines in Science and Technology (2012HB004), and the Research Foundation of the Educational Department of Yunnan Province (2014C134Y).
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Wu, H., Liu, W., Yue, K., Li, J., Huang, W. (2016). Selecting Seeds for Competitive Influence Spread Maximization in Social Networks. In: Che, W., et al. Social Computing. ICYCSEE 2016. Communications in Computer and Information Science, vol 623. Springer, Singapore. https://doi.org/10.1007/978-981-10-2053-7_53
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DOI: https://doi.org/10.1007/978-981-10-2053-7_53
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