Social Network Analysis, Social Big Data and Conspiracy Theories

Caballero, Estrella Gualda

doi:10.4324/9780429452734-1_10

Cited by 5 publications

(3 citation statements)

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“…To develop a comprehensive understanding of the engagements with Uncanny Similarity on Twitter, we complemented the social network analysis with a qualitative content analysis of particularly salient discussions within our dataset (Caballero, 2020: 135–137). This methodological decision was inspired by calls to experiment with new combinations of quantitative and qualitative methods when studying digitally networked phenomena and information diffusion in digital publics in particular (Moats & Borra, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…However, when publishing and promoting preprints, their uncertain epistemic status can induce unintended and potentially negative effects. One of these unintended effects is the advancement of conspiracy theories on social media platforms (Papakyriakopoulos et al, 2020; Caballero, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…A growing body of literature addresses the activities of conspiracy theorists on social media (Bangerter et al, 2020; Caballero, 2020; Uscinski et al, 2018). Some of this work examines the forms of engagement with scientific knowledge that social media platforms afford to conspiracy theories and theorists.…”

Section: Introductionmentioning

confidence: 99%

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Clickbait or conspiracy? How Twitter users address the epistemic uncertainty of a controversial preprint

Bauer,

Heimstädt,

Franzreb

et al. 2023

Big Data & Society

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Many scientists share preprints on social media platforms to gain attention from academic peers, policy-makers, and journalists. In this study we shed light on an unintended but highly consequential effect of sharing preprints: Their contribution to conspiracy theories. Although the scientific community might quickly dismiss a preprint as insubstantial and ‘clickbaity’, its uncertain epistemic status nevertheless allows conspiracy theorists to mobilize the text as scientific support for their own narratives. To better understand the epistemic politics of preprints on social media platforms, we studied the case of a biomedical preprint, which was shared widely and discussed controversially on Twitter in the wake of the coronavirus disease 2019 pandemic. Using a combination of social network analysis and qualitative content analysis, we compared the structures of engagement with the preprint and the discursive practices of scientists and conspiracy theorists. We found that despite substantial engagement, scientists were unable to dampen the conspiracy theorists’ enthusiasm for the preprint. We further found that members from both groups not only tried to reduce the preprint's epistemic uncertainty but sometimes deliberately maintained it. The maintenance of epistemic uncertainty helped conspiracy theorists to reinforce their group's identity as skeptics and allowed scientists to express concerns with the state of their profession. Our study contributes to research on the intricate relations between scientific knowledge and conspiracy theories online, as well as the role of social media platforms for new genres of scholarly communication.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%