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.
翻译：社会影响是复杂社会环境中观点变化的特点,结合了个人过去的立场和人际影响通过社会网络影响的影响。在这项工作中,我们观察到了2020年4月至2021年5月推特上对冠状病毒疫苗的态度变化,在Twitter上,有1 ⁇ 代理表现出了翻转的姿态行为,其中53.7 ⁇ 被确认为机器人。然后我们提出了一个新的社会影响模式,以描述代理人立场变化的特点。这个模式考虑了代理人及其邻居以往的推文和总体网络结构,以达到姿态分数。在我们的实验中,模型达到了86 ⁇ 的准确度。在我们的分析中,机器人代理需要较少的社会影响才能翻转立场,而更多的机器人翻动。
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