Deep State Phobia. Narrative Convergence in Coronavirus Conspiracism on Instagram
Tuters, M., & Willaert, T. (2022). Deep State Phobia. Narrative Convergence in Coronavirus Conspiracism on Instagram. Convergence: The International Journal of Research into New Media Technologies, 28(4), 1214-1238. https://doi.org/10.1177/13548565221118751
Recent scholarship has established that conspiracist narratives proliferated in mainstream online discourse during the coronavirus pandemic. This proliferation has been provocatively characterized as a ‘conspiracy singularity’ in which previously divergent conspiracy narratives converged into a single, overarching narrative. Yet while the idea of narrative convergence has long figured in conspiracy theory research, empirical evidence has been scarce. The present article aims to address this gap by means of an investigation of an archive containing over 470,000 conspiracy-related Instagram posts from 2020. Given the size and conceptual complexity of the dataset, the paper introduces a ‘digital hermeneutics’ approach, which combines data science methods with qualitative interpretation and theorization. Operating across three levels of observation (hashtag analysis, text analysis, and image analysis) we identify patterns of convergence among different conspiracy narratives (including anti-vax, QAnon, anti-5G, and ‘The Great Reset’) over the year 2020 as well as the apparent role of protagonists and antagonists (notably Donald Trump and Bill Gates) in creating connections. In interpreting these findings we focus on the concept of ‘the Deep State’ as a bridge between various conspiracist narratives, which seems to cut diagonally across political ideologies.