How disinformation operations against Russian opposition leader Alexei Navalny influence the international audience on Twitter

Abstract

Previous research dedicated a lot of effort to investigation of the activities of the Internet Research Agency, a Russia-based troll factory, as well as other information operations. However, those studies are mostly focused on the 2016 U.S. presidential election, Brexit, and other major international political events. In this study, we have attempted to analyze how narratives about a domestic issue in Russia are used by malicious actors to promote harmful discourses globally and persuade an international audience on Twitter. We have identified bot and troll activities related to the Twitter discussions of a Russian opposition leader Alexei Navalny using social network analysis and bot detection. We have also implemented the BEND framework to find persuasion maneuvers that are used by bots in conversations about Navalny and found attempts to manipulate the opinion of the international audience on Twitter. Our findings have demonstrated that there is a significant presence of bot activities in information operations against Alexei Navalny as one of the leaders of the Russian opposition. We have observed how the Russian domestic issue is framed in the context of Russian confrontation with the West and how it is used to promote hostile narratives either against Navalny, an opposition movement, or democratic values. Many agents that we have identified pretend to be English speakers, who exhibit hostile attitudes towards Navalny and the Western democracies, express skepticism and distort the facts, promote a lack of trust in the democratic institutions as well as spread disinformation and conspiracy theories.

Bots Versus Humans: Discursive Activism During the Pandemic in the Iranian Twittersphere

“…In contrast to other contexts, such as the study by Duan et al (2022) and Ferrara (2020), Iranian users (bot or human) were less inclined to propagate conspiracy theories during this politically contentious period, choosing instead to channel their efforts into their political goals. Our results also echoes other researches in India (Neyazi, 2020) and Russia (Alieva et al, 2022; Stukal et al, 2017) showing that bots use more hashtags and disseminate particular hashtags to infiltrate the flow on information on Twitter.…”

“…Existing research in this field highlights the use of bots to discredit opposition politicians, manipulate popularity metrics, and amplify particular messages and narratives. Since research is conclusive in such debates, whether in democratic societies (Howard & Kollanyi, 2016;Howard et al, 2018;, non-democratic societies (Alieva et al, 2022;Stukal et al,2017Stukal et al, , 2019Vasilkova & Legostaeva, 2019), or more particularly in Iran (Farzam et al, 2022;Honari & Alinejad, 2022;Thieltges et al, 2018), our primary aim was not to replicate them and solely investigate bots' behavior and quantitative measures. Instead, we seek to contribute to the growing body of literature in this field by investigating bots' discursive activism and the similarities and differences of them with human activism during the pandemic.…”

The Evolution of Authoritarianism and Contentious Action in Russia

“…Twitter in Russia is considerably lower compared to the more popular social network, VK, especially outside of Moscow and Saint Petersburg, Twitter remains a key platform for opposition activists and politicians to communicate with their audiences (Alieva et al, 2022;Dollbaum, 2021b) and overseas users, for example, English speakers or Russians living overseas. Alexanyan et al (2012) argue that Twitter users form distinct clusters and maintain user communities within Russian regions, fostering more consistent engagement and community formation.…”

SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter

“…Twitter serves as one of the most widely-used social media platforms; however, the widespread features in recent years have also led to the rapid growth of anomalous users. For instance, abnormal users often initiate campaigns to pursue malicious goals, which violates the principles of healthy online discussions on social media platforms (Alieva, Moffitt, and Carley 2022). One of the most common types of anomalous users is bots, identified at 9% to 15% of active users (Varol et al 2017).…”