National Security : Social Media Disinformation Campaigns Against US Military Personnel and Veterans

Social media provides political news and information for both active duty military personnel and veterans. We analyze the subgroups of Twitter and Facebook users who spend time consuming junk news from websites that target US military personnel and veterans with conspiracy theories, misinformation, and other forms of junk news about military affairs and national security issues. (1) Over Twitter we find that there are significant and persistent interactions between current and former military personnel and a broad network of extremist, Russia-focused, and international conspiracy subgroups. (2) Over Facebook, we find significant and persistent interactions between public pages for military and veterans and subgroups dedicated to political conspiracy, and both sides of the political spectrum. (3) Over Facebook, the users who are most interested in conspiracy theories and the political right seem to be distributing the most junk news, whereas users who are either in the military or are veterans are among the most sophisticated news consumers, and share very little junk news through the network. US MILITARY PERSONNEL, VETERANS AND SOCIAL MEDIA Social media are an important means of communication for both active duty military personnel and veterans. When on assignment, platforms like Facebook and Twitter can allow service personnel to stay in touch with family and friends back home. After service, social media allow soldiers and support staff to stay in touch with their colleagues and friends from their period of service, which performs an important role in veteran transition into civilian life. The pubic tends to place trust in military personnel and veterans, making them potentially influential voters and community leaders. Given this trust and their role in ensuring national security, these individuals have the potential to become particular targets for influence operations and information campaigns conducted on social media. There are already reports of US service personnel being confronted by foreign intelligence agencies while posted abroad, with details of their personal lives gleaned from social media. We set about mapping the influence of known sources of junk political news and information that regularly craft content for an audience of US military personnel and veterans–we call such activity Veteran Operations or “VetOps”. In particular, we investigate patterns of interaction between current or former military personnel who have (i) shared junk news targeted to an audience of military personnel, (ii) engaged with users who disseminate large amounts of misinformation about national security and international affairs. SOCIAL NETWORK MAPPING Visualizing social network data is one of the most powerful ways of understanding how people pass information and associate with one another. By using selected keywords, seed accounts, and known links to content, it is possible to construct large network visualizations. The underlying networks of these visualizations can then be manipulated to find communities of accounts and clusters of association. Importantly, one can then tag these associated clusters of accounts and content with political attributes based on knowledge of account history, content type, and association metrics. Each map of social networks constructed over Twitter and Facebook allows for insight into both social structure and flow of information. In this study, we use the Graphika visualization suite to map and tag accounts based around prominent political accounts, topics, political affiliations, and geographical areas. Successfully mapping social networks also allows us to catalogue users and content and generate both descriptive statistics and statistical models that explain changes in network structure. Social network maps are composed of “nodes” which represent the social media accounts in question. Each node is connected to one or more further nodes in the map via social relationships; digital interactions between accounts. These maps then represent patterns of connections between nodes via a Fruchterman-Reingold visualization algorithm. This visualization algorithm works to place nodes in a map onto a canvas according to two principles: first, a “centrifugal force” acts upon each node to push it to the edge of the canvas; second, a “cohesive force” acts upon every connected pair of nodes to pull them closer together. Each node in these networks belongs to a group with a shared pattern of interests, such as a collection of Facebook accounts that all like US pro-Donald Trump political pages, for example. A group is a collection of segments that are geographically, culturally, or socially similar. For example, a segment of US Trump supporters, US Libertarians, and US Constitutional Conservatives could be grouped into a “US Conservatives” group. The method of segmenting users, coding groups, and generating broad observations about association is an iterative process that involves qualitative, quantitative