Public Opinion Dynamics in Cyberspace on Russia–Ukraine War: A Case Analysis With Chinese Weibo
Bingyang Chen, Xiao Wang, Weishan Zhang, Tao Chen, Chenyu Sun, Zhenqi Wang, Fei–Yue Wang
Abstract
The intensity and scale of the opinion fightings in cyberspace on the Russia–Ukraine war (RUW) have opened a new chapter in the history of world warfare. This is a magnificent demonstration of social cognitive war fighting with cyber-physical-social systems (CPSS) that would impact our humankind significantly now and for a long time to come, not just on our understanding of wars, but every aspect of our life. Therefore, it is worth of studying the opinion dynamics of the RUW in the cyberspace. This article will start this direction with an analysis of the evolutionary dynamics of the public opinion fighting, only using Chinese Weibo texts as a case study due to the time constraint. It first clusters the Weibo texts into four categories with unsupervised learning method using Latent Dirichlet Allocation and then collects opinions by extracting keywords. Meanwhile, an opinion adversarial evolution algorithm is proposed to dynamically model the dominance degree of an opinion in the evolutionary processes. We release a dataset of Chinese Weibo associated with RUW. The proposed approach of modeling and analyzing data-driven public opinion dynamics provides a new way for accessing opinion warfare in CPSS.