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Influence Propagation Based Influencer Detection in Online Forum

Wen GU, Shohei KATO, Fenghui REN, Guoxin SU, Takayuki ITO, Shinobu HASEGAWA

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Summary :

Influential user detection is critical in supporting the human facilitator-based facilitation in the online forum. Traditional approaches to detect influential users in the online forum focus on the statistical activity information such as the number of posts. However, statistical activity information cannot fully reflect the influence that users bring to the online forum. In this paper, we propose to detect the influencers from the influence propagation perspective and focus on the influential maximization (IM) problem which aims at choosing a set of users that maximize the influence propagation from the entire social network. An online forum influence propagation network (OFIPN) is proposed to model the influence from an individual user perspective and influence propagation between users, and a heuristic algorithm that is proposed to find influential users in OFIPN. Experiments are conducted by simulations with a real-world social network. Our empirical results show the effectiveness of the proposed algorithm.

Publication
IEICE TRANSACTIONS on Information Vol.E106-D No.4 pp.433-442
Publication Date
2023/04/01
Publicized
2022/11/07
Online ISSN
1745-1361
DOI
10.1587/transinf.2022IIP0010
Type of Manuscript
Special Section PAPER (Special Section on Intelligent Information Processing to Solve Social Issues)
Category

Authors

Wen GU
  Japan Advanced Institute of Science and Technology
Shohei KATO
  Nagoya Institute of Technology
Fenghui REN
  University of Wollongong
Guoxin SU
  University of Wollongong
Takayuki ITO
  Kyoto University
Shinobu HASEGAWA
  Japan Advanced Institute of Science and Technology

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