The Russian state-funded international broadcaster RT (formerly Russia Today) has attracted much attention as a purveyor of Russian propaganda. To date, most studies of RT have focused on its broadcast, website, and social media content, with little research on its audiences. Through a data-driven application of network science and other computational methods, we address this gap to provide insight into the demographics and interests of RT’s Twitter followers, as well as how they engage with RT. Building upon recent studies of Russian state-sponsored media, we report three main results. First, we find that most of RT’s Twitter followers only very rarely engage with its content and tend to be exposed to RT’s content alongside other mainstream news channels. This indicates that RT is not a central part of their online news media environment. Second, using probabilistic computational methods, we show that followers of RT are slightly more likely to be older and male than average Twitter users, and they are far more likely to be bots. Third, we identify thirty-five distinct audience segments, which vary in terms of their nationality, languages, and interests. This audience segmentation reveals the considerable heterogeneity of RT’s Twitter followers. Accordingly, we conclude that generalizations about RT’s audience based on analyses of RT’s media content, or on vocal minorities among its wider audiences, are unhelpful and limit our understanding of RT and its appeal to international audiences.

作为俄罗斯宣传的传播者，俄罗斯国家资助的国际广播公司RT（以前的“今日俄罗斯”）引起了很多关注。迄今为止，RT的大多数研究都集中在其广播，网站和社交媒体内容上，而对受众的研究很少。通过数据驱动的网络科学和其他计算方法的应用，我们解决了这一空白，以洞悉RT的Twitter关注者的人口统计和兴趣以及他们如何与RT互动。基于对俄罗斯国家赞助媒体的最新研究，我们报告了三个主要结果。首先，我们发现RT的大多数Twitter关注者很少参与其内容，并且倾向于与其他主流新闻频道一起接触RT的内容。这表明RT并不是其在线新闻媒体环境的核心部分。第二，使用概率计算方法，我们显示RT的追随者比普通的Twitter用户更可能是年龄较大和男性，而且他们更可能是机器人。第三，我们确定了35个不同的受众群体，这些受众群体的国籍，语言和兴趣不同。受众细分显示了RT的Twitter关注者的异质性。因此，我们得出结论，基于对RT媒体内容的分析或基于RT广大受众中的声乐少数群体的概括，对RT受众的概括是无济于事的，并限制了我们对RT的理解及其对国际受众的吸引力。我们确定了35个不同的受众群体，这些受众群体的国籍，语言和兴趣不同。受众细分显示了RT的Twitter关注者的异质性。因此，我们得出结论，基于对RT媒体内容的分析或基于RT广大受众中的声乐少数群体的概括，对RT受众的概括是无济于事的，并限制了我们对RT的理解及其对国际受众的吸引力。我们确定了35个不同的受众群体，这些受众群体的国籍，语言和兴趣不同。受众细分显示了RT的Twitter关注者的异质性。因此，我们得出结论，基于对RT媒体内容的分析或基于RT广大受众中的声乐少数群体的概括，对RT受众的概括是无济于事的，并限制了我们对RT的理解及其对国际受众的吸引力。