Topic-based Social Influence Measurement for Social Networks

Authors

• Asso Hamzehei, CSE, UNSW Data61, CSIROFollow
• Shanqing Jiang, CSE, UNSWFollow
• Danai Koutra, University of Michigan, USAFollow
• Raymond Wong, CSE, UNSWFollow
• Fang Chen, Data61, CSIRO CSE, UNSWFollow

Author ORCID Identifier

Asso Hamzehei https://orcid.org/0000-0003-0267-7771
Shanqing Jiang
Danai Koutra
Raymond Wong
Fang Chen

Document Type

Selected papers from the Australasian Conference on Data Mining (AUSDM)

Abstract

Social science studies have acknowledged that the social influence of individuals is not identical. Social networks structure and shared text can reveal immense information about users, their interests, and topic-based influence. Although some studies have considered measuring user influence, less has been on measuring and estimating topic-based user influence. In this paper, we propose an approach that incorporates network structure, user-generated content for topic-based influence measurement, and user’s interactions in the network. We perform experimental analysis on Twitter data and show that our proposed approach can effectively measure topic-based user influence.

Recommended Citation

Hamzehei, Asso; Jiang, Shanqing; Koutra, Danai; Wong, Raymond; and Chen, Fang (2017) "Topic-based Social Influence Measurement for Social Networks," The Australasian Journal of Information Systems: Vol. 21: No. 1, Article 49.
DOI: 10.3127/ajis.v21i0.1552
Available at: https://aisel.aisnet.org/ajis/vol21/iss1/49