Social influence characterizes the change of opinions in a complex social environment, incorporating an individual's past stances and the impact of interpersonal influence through the social network influence. In this work, we observe stance changes towards the coronavirus vaccine on Twitter from April 2020 to May 2021, where 1\% of the agents exhibit the stance flipping behavior, of which 53.7\% are identified bots. We then propose a novel social influence model to characterize the change in stance of agents. This model considers an agent's and his neighbor's past tweets and the overall network structure towards a stance score. In our experiments, the model achieves 86\% accuracy. In our analysis, bot agents require lesser social influence to flip stances and a larger proportion of bots flip.
Flipping Stance: Social Influence on Bot's and Non Bot's COVID Vaccine Stance