UGGreedy:Influence Maximization for User Group in Microblogging

YU Miao; YANG Wu; WANG Wei; SHEN Guowei; DONG Guozhong; GONG Liangyi

doi:10.1049/cje.2016.03.008

Volume 25 Issue 2

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YU Miao, YANG Wu, WANG Wei, et al. “UGGreedy:Influence Maximization for User Group in Microblogging”. Chinese Journal of Electronics, vol. 25 no. 2. doi: 10.1049/cje.2016.03.008

Citation:

YU Miao, YANG Wu, WANG Wei, et al. “UGGreedy:Influence Maximization for User Group in Microblogging”. Chinese Journal of Electronics, vol. 25 no. 2. doi: 10.1049/cje.2016.03.008

YU Miao, YANG Wu, WANG Wei, et al. “UGGreedy:Influence Maximization for User Group in Microblogging”. Chinese Journal of Electronics, vol. 25 no. 2. doi: 10.1049/cje.2016.03.008

Citation:

YU Miao, YANG Wu, WANG Wei, et al. “UGGreedy:Influence Maximization for User Group in Microblogging”. Chinese Journal of Electronics, vol. 25 no. 2. doi: 10.1049/cje.2016.03.008

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UGGreedy:Influence Maximization for User Group in Microblogging

doi: 10.1049/cje.2016.03.008

1.
Information Security Research Center, Harbin Engineering University, Harbin 150001, China;
2.
College of Computer Science and Technology, Guizhou University, Guiyang 550025, China

Funds: This work is supported by the National Natural Science Foundation of China (No.61170242, No.61572459), and the National High Technology Research and Development Program of China (863 Program) (No.2012AA012802).

More Information

Corresponding author: YANG Wu (corresponding author) was born in 1974. He is currently a professor and Ph.D. supervisor in the Harbin Engineering University. His main research interests include data mining, information security and wireless sensor network, etc. (Email:yangwu@hrbeu.edu.cn)
Received Date: 2015-07-01
Rev Recd Date: 2015-11-05
Publish Date: 2016-03-10

Abstract

Abstract

We study a new influence maximization problem about how to find a seed set which can maximize the influence spread to a targeted user group in microblogging. To solve this problem, we propose a threestage User group greedy algorithm (UGGreedy) based on user attributes. To reduce network scale, we delete useless user nodes, and rank the rest of users based on user attributes to form a seed candidate set. We employ the seed candidate set to construct a simplified microblogging network graph.We propose a novel influence greedy algorithm based on influence accumulation spread to find the seed set. Experimental results show that UGGreedy can achieve remarkable efficiency on the influence maximization problem for user group in real microblogging networks.
- Microblogging,
- User attribute,
- User group,
- Influence maximization

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References(12)

References

WANG Jing, LIU Zhijing and ZHAO Hui, "Micro-blogs entity recognition based on DSTCRF", Chinese Journal of Electronics, Vol.23, No.1, pp.147-150, 2014.

YANG Zhen, FAN Kefeng, LAI Yingxu, GAO Kaiming and WANG Yong, "Short texts classification through reference document expansion", Chinese Journal of Electronics, Vol.23, No.2, pp.315-321, 2014.

D. Kempe, J. Kleinberg and E. Tardos, "Maximizing the spread of influence through a social network", Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, pp.137-146, 2003.

J. Leskovec, A. Krause, C. Guestrin, et al., "Cost-effective outbreak detection in networks", Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, USA, pp.420-429, 2007.

P. Domingos and M. Richardson, "Mining the network value of customers", Seventh International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, pp.57-66, 2001.

W. Chen, Y. Wang and S. Yang, "Efficient influence maximization in social networks", Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, pp.199-208, 2009.

W. Chen, C.Wang and Y.Wang, "Scalable influence maximization for prevalent viral marketing in large-scale social networks", Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, pp.1029-1038, 2010.

S. Cheng, H. Shen, J. Huang, W. Chen and X. Cheng, "Automatic classification of input/output access patterns", IMRank: Influence Maximization via Finding Self-Consistent Ranking, Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval, Gold Coast, Queensland, Australia, pp.475-484, 2014.

R. Ghosh, T. Surachawala and K. Lerman, "Entropy-based classification of retweeting activity on Twitter", The 4th SNA-KDD Workshop, San Diego, CA, USA, 2011.

S. Wu, J.M. Hofman, W.A. Mason and D.J. Watts, "Who says what to whom on Twitter", Proceedings of the 20th International Conference on World Wide Web, Hyderabad, India, pp.705-714, 2011.

H. Kwak, C. Lee, Hosung Park and Sue Moon, "What is Twitter, a social network or a news media", Proceedings of the 19th International Conference on World Wide Web, Raleigh, North Carolina, USA, pp.591-600, 2010.

S. Brin and L. Page, "The anatomy of a large-scale hypertextual web search engine", Computer Networks and ISDN Systems, Vol.30, pp.107-117, 1998.

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