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

Authors : Mareike Bauer, Maximilian Heimstädt, Carlos Franzreb, Sonja Schimmler

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.

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


FAIREST: A Framework for Assessing Research Repositories

Authors : Mathieu d’Aquin, Fabian Kirstein, Daniela Oliveira, Sonja Schimmler, Sebastian Urbanek

The open science movement has gained significant momentum within the last few years. This comes along with the need to store and share research artefacts, such as publications and research data. For this purpose, research repositories need to be established.

A variety of solutions exist for implementing such repositories, covering diverse features, ranging from custom depositing workflows to social media-like functions.

In this article, we introduce the FAIREST principles, a framework inspired by the well- known FAIR principles, but designed to provide a set of metrics for assessing and selecting solutions for creating digital repositories for research artefacts. The goal is to support decision makers in choosing such a solution when planning for a repository, especially at an institutional level.

The metrics included are therefore based on two pillars: (1) an analysis of established features and functionalities, drawn from existing dedicated, general purpose and commonly used solutions, and (2) a literature review on general requirements for digital repositories for research artefacts and related systems.

We further describe an assessment of 11 widespread solutions, with the goal to provide an overview of the current landscape of research data repository solutions, identifying gaps and research challenges to be addressed.