报告题目：Dynamic Opinion Maximization in Social Networks
时间：2021-11-20（星期六）08:30～11:30
地点：腾讯会议室（ID：946 422 608）
主讲：王兴伟教授
主办：福建省网络安全与密码技术重点实验室、计算机与网络空间安全学院
参加对象：感兴趣的教师和学生
报告摘要：Opinion Maximization (OM) aims at determining a small set of influential individuals, spreading the expected opinions of an object (e.g., product or individual) to their neighbors through the social relationships and eventually producing the largest rational opinion spread. In previous studies, once the corresponding nodes are activated, their opinions usually keep unchanged, which fails to capture the real scenarios where the opinion of each node on the object can dynamically change over time. In this view, we propose a Dynamic Opinion Maximization Framework (DOMF) to settle the OM problem, which consists of two parts: dynamic opinion formation and adaptive seeding process. Specifically, we formulate the OM problem by maximizing rational opinions. To model the dynamic opinion issue, we propose adaptive cooperation model based on Q-learning theory, which is proved to be capable of eventually reaching convergence. Moreover, to dynamically generate the initial seed nodes, we design the Multi-stage Heuristic Algorithm (MHA). Experimental results on eight network datasets demonstrate that each component of our model is effective, and the proposed approach improves the rational opinion spread over the state-of-the-art methods.
报告人简介：
Xingwei Wang received the B.S., M.S., and Ph.D. degrees in computer science from the Northeastern University, Shenyang, China in 1989, 1992, and 1998 respectively. He is currently a Professor at the College of Computer Science and Engineering, Northeastern University, Shenyang, China. He is the winner of National Science Fund for Distinguished Young Scholars of China and the Fellow of China Institute of Communications. His research interests include cloud computing and future Internet, etc. He has published more than 100 journal articles, books and book chapters, and refereed conference papers. He has received several best paper awards.
