Russian propaganda on social media during the 2022 invasion of Ukraine

IF 3 2区 计算机科学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS EPJ Data Science Pub Date : 2023-09-12 DOI:10.1140/epjds/s13688-023-00414-5
Dominique Geissler, Dominik Bär, Nicolas Pröllochs, Stefan Feuerriegel
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引用次数: 23

Abstract

Abstract The Russian invasion of Ukraine in February 2022 was accompanied by practices of information warfare, yet existing evidence is largely anecdotal while large-scale empirical evidence is lacking. Here, we analyze the spread of pro-Russian support on social media. For this, we collected $N = 349{,}455$ N = 349 , 455 messages from Twitter with pro-Russian support. Our findings suggest that pro-Russian messages received ∼251,000 retweets and thereby reached around 14.4 million users. We further provide evidence that bots played a disproportionate role in the dissemination of pro-Russian messages and amplified its proliferation in early-stage diffusion. Countries that abstained from voting on the United Nations Resolution ES-11/1 such as India, South Africa, and Pakistan showed pronounced activity of bots. Overall, 20.28% of the spreaders are classified as bots, most of which were created at the beginning of the invasion. Together, our findings suggest the presence of a large-scale Russian propaganda campaign on social media and highlight the new threats to society that originate from it. Our results also suggest that curbing bots may be an effective strategy to mitigate such campaigns.

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2022年入侵乌克兰期间,俄罗斯在社交媒体上的宣传
俄罗斯2022年2月入侵乌克兰伴随着信息战的实践,但现有证据大多是轶事,缺乏大规模的经验证据。在这里,我们分析亲俄支持在社交媒体上的传播。为此,我们从支持亲俄的Twitter上收集了$N = 349{,}455$ N = 349, 455条消息。我们的研究结果表明,亲俄信息获得了约251,000次转发,从而达到了约1440万用户。我们进一步提供证据表明,机器人在亲俄信息的传播中发挥了不成比例的作用,并在传播的早期阶段扩大了其扩散。对联合国ES-11/1号决议投弃权票的国家,如印度、南非、巴基斯坦等,显示出明显的机器人活动。总体而言,20.28%的传播器被归类为机器人,其中大多数是在入侵开始时创建的。总之,我们的研究结果表明,俄罗斯在社交媒体上开展了大规模的宣传活动,并强调了由此产生的对社会的新威胁。我们的研究结果还表明,遏制机器人可能是减轻此类活动的有效策略。
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来源期刊
EPJ Data Science
EPJ Data Science MATHEMATICS, INTERDISCIPLINARY APPLICATIONS -
CiteScore
6.10
自引率
5.60%
发文量
53
审稿时长
13 weeks
期刊介绍: EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.
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