Agents of Discord: Modeling the Impact of Political Bots on Opinion Polarization in Social Networks

IF 3 2区 社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Hsiu-Chi Lu, Hsuan-wei Lee
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Abstract

The pervasive presence and influence of political bots have become the subject of extensive research in recent years. Studies have revealed that a significant percentage of active accounts are bots, contributing to the polarization of public sentiment online. This study employs an agent-based model in conducting computer simulations of complex social networks, to elucidate how bots, representing diverse ideological perspectives, exacerbate societal divisions. To investigate the dynamics of opinion diffusion and shed light on the phenomenon of polarization caused by the activities of political bots, we introduced bots into a bounded-confidence opinion dynamic model for different social networks, whereby the effects of bots on other agents were studied to provide a comprehensive understanding of their influence on opinion dynamics. The simulations showed that the symmetrical deployment of bots on both sides of the opinion spectrum intensifies polarization. These effects were observed within specific tolerance and homophily ranges, with low and high user tolerances slowing down polarization. Moreover, the average path length of the network and the centrality of the bots had a significant impact on the result. Finally, polarization tends to be lower when humans exhibit reduced confidence in bots. This research not only offers valuable insights into the implications of bot activities on the polarization of public opinion and current state of digital society but also provides suggestions to mitigate bot-driven polarization.
不和谐代理:模拟政治机器人对社交网络舆论两极分化的影响
政治机器人的普遍存在和影响已成为近年来广泛研究的主题。研究显示,活跃账户中有很大一部分是机器人,这加剧了网络上公众情绪的两极分化。本研究采用基于代理的模型对复杂的社交网络进行计算机模拟,以阐明代表不同意识形态观点的机器人是如何加剧社会分化的。为了研究舆论扩散的动态,揭示政治机器人活动造成的两极分化现象,我们将机器人引入不同社交网络的有界信任舆论动态模型,研究机器人对其他代理的影响,以全面了解它们对舆论动态的影响。模拟结果表明,在舆论频谱两侧对称部署机器人会加剧两极分化。这些影响是在特定的容忍度和同质性范围内观察到的,低用户容忍度和高用户容忍度都会减缓极化。此外,网络的平均路径长度和机器人的中心性对结果也有显著影响。最后,当人类对机器人的信任度降低时,极化程度也会降低。这项研究不仅就机器人活动对舆论极化和数字社会现状的影响提供了宝贵的见解,还为缓解机器人驱动的极化提供了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Social Science Computer Review
Social Science Computer Review 社会科学-计算机:跨学科应用
CiteScore
9.00
自引率
4.90%
发文量
95
审稿时长
>12 weeks
期刊介绍: Unique Scope Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of informational technology. Topics included: artificial intelligence, business, computational social science theory, computer-assisted survey research, computer-based qualitative analysis, computer simulation, economic modeling, electronic modeling, electronic publishing, geographic information systems, instrumentation and research tools, public administration, social impacts of computing and telecommunications, software evaluation, world-wide web resources for social scientists. Interdisciplinary Nature Because the Uses and impacts of computing are interdisciplinary, so is Social Science Computer Review. The journal is of direct relevance to scholars and scientists in a wide variety of disciplines. In its pages you''ll find work in the following areas: sociology, anthropology, political science, economics, psychology, computer literacy, computer applications, and methodology.
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