Influence Propagation Based Influencer Detection in Online Forum

Publication Name

IEICE Transactions on Information and Systems

Abstract

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.

Open Access Status

This publication may be available as open access

Volume

E106D

Issue

4

First Page

433

Last Page

442

Funding Sponsor

Nagoya Institute of Technology

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Link to publisher version (DOI)

http://dx.doi.org/10.1587/TRANSINF.2022IIP0010