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Identifying Influencers in Social Networks

Software College, Northeastern University, Shenyang 110169, China
Author to whom correspondence should be addressed.
Entropy 2020, 22(4), 450;
Received: 20 March 2020 / Revised: 9 April 2020 / Accepted: 13 April 2020 / Published: 15 April 2020
(This article belongs to the Special Issue Social Networks and Information Diffusion II)
Social network analysis is a multidisciplinary research covering informatics, mathematics, sociology, management, psychology, etc. In the last decade, the development of online social media has provided individuals with a fascinating platform of sharing knowledge and interests. The emergence of various social networks has greatly enriched our daily life, and simultaneously, it brings a challenging task to identify influencers among multiple social networks. The key problem lies in the various interactions among individuals and huge data scale. Aiming at solving the problem, this paper employs a general multilayer network model to represent the multiple social networks, and then proposes the node influence indicator merely based on the local neighboring information. Extensive experiments on 21 real-world datasets are conducted to verify the performance of the proposed method, which shows superiority to the competitors. It is of remarkable significance in revealing the evolutions in social networks and we hope this work will shed light for more and more forthcoming researchers to further explore the uncharted part of this promising field. View Full-Text
Keywords: complex network; social network analysis; multilayer network; node influence complex network; social network analysis; multilayer network; node influence
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MDPI and ACS Style

Huang, X.; Chen, D.; Wang, D.; Ren, T. Identifying Influencers in Social Networks. Entropy 2020, 22, 450.

AMA Style

Huang X, Chen D, Wang D, Ren T. Identifying Influencers in Social Networks. Entropy. 2020; 22(4):450.

Chicago/Turabian Style

Huang, Xinyu; Chen, Dongming; Wang, Dongqi; Ren, Tao. 2020. "Identifying Influencers in Social Networks" Entropy 22, no. 4: 450.

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