Opinion Optimization in Directed Social Networks

Authors

  • Haoxin Sun Fudan University
  • Zhongzhi Zhang Fudan University

DOI:

https://doi.org/10.1609/aaai.v37i4.25585

Keywords:

DMKM: Graph Mining, Social Network Analysis & Community Mining, CSO: Constraint Optimization, SO: Sampling/Simulation-Based Search

Abstract

Shifting social opinions has far-reaching implications in various aspects, such as public health campaigns, product marketing, and political candidates. In this paper, we study a problem of opinion optimization based on the popular Friedkin-Johnsen (FJ) model for opinion dynamics in an unweighted directed social network with n nodes and m edges. In the FJ model, the internal opinion of every node lies in the closed interval [0, 1], with 0 and 1 being polar opposites of opinions about a certain issue. Concretely, we focus on the problem of selecting a small number of k<
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Published

2023-06-26

How to Cite

Sun, H., & Zhang, Z. (2023). Opinion Optimization in Directed Social Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 37(4), 4623-4632. https://doi.org/10.1609/aaai.v37i4.25585

Issue

Vol. 37 No. 4: AAAI-23 Technical Tracks 4

Section

AAAI Technical Track on Data Mining and Knowledge Management