An Efficient Evolutionary User Interest Community Discovery Model in Dynamic Social Networks for Internet of People.pdf (555.97 kB)
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An Efficient Evolutionary User Interest Community Discovery Model in Dynamic Social Networks for Internet of People

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journal contribution
posted on 26.03.2020, 13:28 by Liang Jiang, Leilei Shi, Lu Liu, Jingjing Yao, Bo Yuan, Yongjun Zheng
Internet of People (IoP), which focuses on personal information collection by a wide range of the mobile applications, is the next frontier for Internet of Things. Nowadays, people become more and more dependent on the Internet, increasingly receiving and sending information on social networks (e.g., Twitter, etc.); thus social networks play a decisive role in IoP. Therefore, community discovery has emerged as one of the most challenging problems in social networks analysis. To this end, many algorithms have been proposed to detect communities in static networks. However, microblogging social networks are extremely dynamic in both content distribution and topological structure. In this paper, we propose a model for efficient evolutionary user interest community discovery which employs a nature-inspired genetic algorithm to improve the quality of community discovery. Specifically, a preprocessing method based on hypertext induced topic search improves the quality of initial users and posts, and a label propagation method is used to restrict the conditions of the mutation process to further improve the efficiency and effectiveness of user interest community detection. Finally, the experiments on the real datasets validate the effectiveness of the proposed model.

History

Citation

IEEE Internet of Things Journal, Volume 6, Issue: 6, Dec. 2019

Author affiliation

Department of Informatics

Version

AM (Accepted Manuscript)

Published in

IEEE Internet of Things Journal

Volume

6

Issue

6

Pagination

9226 - 9236

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

eissn

2372-2541

Copyright date

2019

Available date

17/01/2019

Publisher version

https://ieeexplore.ieee.org/document/8616896

Language

en