Challenges and Opportunities to Counter Information Operations Through Social Network Analysis and Theory

Information operations on social media have recently attracted the attention of media outlets, research organizations and governments, given the proliferation of high-profile cases such as the alleged foreign interference in the 2016 US presidential election. Nation-states and multilateral organizations continue to face challenges while attempting to counter false narratives, due to lack of familiarity and experience with online environments, limited knowledge and theory of human interaction with and within these spaces, and the limitations imposed by those who own and maintain social media platforms. In particular, these attributes present unique difficulties for the identification and attribution of campaigns, tracing information flows at scale, and identifying spheres of influence. Complications include the anonymity and competing motivations of online actors, poorly understood platform dynamics, and the sparsity of information regarding message transferal across communication platforms. We propose that the use of social network analysis (SNA) can aid in addressing some of these challenges. We begin by providing a brief explanation of the field and its utility in understanding online communications. We discuss how theories drawn from SNA, which seek to make statistical inferences about relationships and information transfer, can be applied to the information operations domain. Specifically, we will focus on how current research in social influence, information diffusion, and cluster analysis can be immediately applied and identify opportunities for future research. We then demonstrate how these analytic techniques can work in practice, utilizing multiple online communication datasets. Finally, we conclude by discussing how the use of these methods can lead to the development of tactical approaches countering misinformation campaigns.