UMD Distinguished Scholar-Teacher Lecture October 2021 https://sway.office.com/sl2qEYQSCN42sLwB
Download my 2021 APSA paper with background material here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3934064
Presentation at the 2019 American Political Science Association Annual Meeting
Download paper here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3445180
#Kremlin: Using Hashtags to Analyze Russian Disinformation and Audience Engagement
By Sarah Oates and John Gray
Reports of Russian interference in U.S. elections have raised grave concerns about the spread of foreign disinformation on social media sites, but there is little detailed analysis that links traditional political communication theory to social media analytics. As a result, it is difficult for researchers and analysts to gauge the nature or level of this threat that is disseminated via the social media. This paper will leverage social science and data science by using traditional content analysis and Twitter analytics to trace how key aspects of Russian strategic narratives were distributed via #MH17, #Donetsk, #russophobia, and #skirpal. This paper proposes flipping the paradigm of many studies that examine Twitter activity essentially in isolation from the communicative goals of the Russian government. Rather, this work highlights how key Russian international communicative goals are expressed through strategic narratives, finds hashtags that reflect those narratives, and analyzes user activity around those hashtags. This approach is not only testing to see how Twitter amplifies specific information goals of the Russians, it also compares the relative success (or failure) of certain hashtags to spread these messages effectively. The research uses the MentionMapp tool (https://mentionmapp.com/), a system that employs network analytics and machine intelligence to identify the behavior of Twitter users as well as generate profiles of users via posting history and connections. The research builds on existing studies of Twitter bots and disinformation to link social network use more directly with strategic narrative goals and forge a way to discuss the relative role of Twitter bots and regular Twitter users in conversations around Russian issues online. As hashtags are an important way for Twitter users to converse and curate their content, this provides a valuable way to gauge how Russian propaganda travels through social media and creates synthetic audience engagement. The study will demonstrate how political communication theory can be used to frame the study of social media; how to relate qualitative content analysis to labels on social media such as Twitter hashtags; and to test the system by examining a set of Russian propaganda narratives as they are represented by hashtags. By examining links between central elements of Russian strategic narratives and the spread of related hashtags, we can move the conversation about Russian influence in the online sphere from conjecture into the realm of measurement and analysis of synthetic audience engagement. There are two key findings from this study. First, some users are consistently active across multiple Kremlin-linked hashtags, suggesting that knowledge of these hashtags is an important way to identify Russian propaganda online influencers. Secondly, the MentionMapp analysis suggests that it is not useful to think of Twitter users in terms of dichotomies such as bot/human or troll/citizen. Rather, the MentionMapp analysis of Twitter activity via hashtags can address the nuances in Twitter use that reflect varying levels of engagement or even awareness in the participation of the spread of foreign disinformation online.