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Abstract: We focus on deriving the underlying generative narrative frameworks in social media posts related to Covid-19 conspiracy theories. Building on earlier work on conspiracies and conspiracy theories, we present an automated pipeline that discovers and aggregates the central actants (people, institutions, places, things) and the interactant relationships that allow us to understand the complex interconnections that narrators build as they move toward creating monological narratives explaining phenomena such as the Covid-19 pandemic. Our model operationalizes aspects of narrative theories first presented by Algirdas Greimas, Joshua Labov and William Waletzky, and Alan Dundes. In this work, we explore the interactions in social media of (i) pre-existing conspiracy theories, such as the globalist cabal behind the pandemic, (ii) emerging conspiracy theories, such as the role 5G telecommunications plays in triggering the virus, and (iii) the intersection or absorption of narratives into totalizing conspiracy theories, such as Q-Anon.

Tim Tangherlini is a professor in the Dept of Scandinavian, and the graduate advisor for the Program in Folklore, at UC Berkeley. His work focuses on computational folkloristics–the data-driven analysis of traditional expressive forms and their circulation on and across social networks. Recent articles include a study of Pizzagate and Bridgegate (PlosOne 2020), and explorations of text reuse in a large corpus of Danish legends. His research has been supported by the NSF, the NIH, the NEH, the ACLS, the JS Guggenheim foundation, and Google. He is the author of many books, including Danish Folktales, Legends, and Other Stories, Talking Trauma: Paramedics and Their Stories, Interpreting Legend: Danish Storytellers and Their Repertoires, and Interpreting Legend: Evald Tang Kristensen’s Legend Informants and Their Repertoires.

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