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  1. Doing your own research and other impossible acts of epistemic superheroism.Andrew Buzzell & Regina Rini - 2023 - Philosophical Psychology 36 (5):906-930.
    The COVID-19 pandemic has been accompanied by an “infodemic” of misinformation and conspiracy theory. This article points to three explanatory factors: the challenge of forming accurate beliefs when overwhelmed with information, an implausibly individualistic conception of epistemic virtue, and an adversarial information environment that suborns epistemic dependence. Normally we cope with the problems of informational excess by relying on other people, including sociotechnical systems that mediate testimony and evidence. But when we attempt to engage in epistemic “superheroics” - withholding trust (...)
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  • Between urgency and data quality: assessing the FAIRness of data in social science research on the COVID-19 pandemic.Veronika Batzdorfer, Wolfgang Zenk-Möltgen, Laura Young, Alexia Katsanidou, Johannes Breuer & Libby Bishop - 2024 - Research Ethics 20 (4):744-763.
    Balancing speed and quality during crises pose challenges for ensuring the value and utility of data in social science research. The COVID-19 pandemic in particular underscores the need for high-quality data and rapid dissemination. Given the importance of behavioural measures and compliance with measures to contain the pandemic, social science research has played a key role in policymaking during this global crisis. This study addresses two key research questions: How FAIR ( findable, accessible, interoperable and reusable) are social science data (...)
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  • Understanding public sentiments and misbeliefs about Sustainable Development Goals: a sentiment and topic modeling analysis.Abhinav Verma & Jogendra Kumar Nayak - 2024 - Journal of Information, Communication and Ethics in Society 22 (2):256-274.
    Misinformation surrounding the Sustainable Development Goals (SDGs) has contributed to the formation of misbeliefs among the public. The purpose of this paper is to investigate public sentiment and misbeliefs about the SDGs on the YouTube platform.,The authors extracted 8,016 comments from YouTube videos associated with SDGs. The authors used a pre-trained Python library NRC lexicon for sentiment and emotion analysis, and to extract latent topics, the authors used BERTopic for topic modeling.,The authors found eight emotions, with negativity outweighing positivity, in (...)
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