TY - JOUR AU - Hamzehei, Asso AU - Jiang, Shanqing AU - Koutra, Danai AU - Wong, Raymond AU - Chen, Fang PY - 2017/11/08 Y2 - 2024/03/29 TI - Topic-based Social Influence Measurement for Social Networks JF - Australasian Journal of Information Systems JA - AJIS VL - 21 IS - 0 SE - Selected Papers from the Australasian Conference on Data Mining (AusDM) DO - 10.3127/ajis.v21i0.1552 UR - https://journal.acs.org.au/index.php/ajis/article/view/1552 SP - AB - 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. ER -