We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Crowdsourcing Knowledge Production of COVID-19 Information on Japanese Wikipedia in the Face of Uncertainty: Empirical Analysis
Summary
Researchers conducted an empirical analysis of COVID-19 article editing patterns on Japanese Wikipedia, finding that science and medicine experts tended to remain silent during periods of high scientific uncertainty. The study suggests that social and political context outweighs purely scientific discussion in shaping high-quality information production under uncertainty.
The results of this study showed that lay experts (ie, Wikipedia editors) in the fields of science and medicine tended to remain silent when facing high scientific uncertainty related to the pandemic. Considering the high quality of the COVID-19-related articles on Japanese Wikipedia, this research also suggested that the sidelining of the science and medicine editors in discussions is not necessarily a problem. Instead, the social and political context of the issues with high scientific uncertainty is more important than the scientific discussions that support accuracy.
Sign in to start a discussion.
More Papers Like This
Introducing an “invisible enemy”: A case study of knowledge construction regarding microplastics in Japanese Wikipedia
Researchers analyzed revision history of the Japanese Wikipedia article on microplastics from 2014 to 2020, finding that editors were reluctant to update content with the latest science and that knowledge construction was shaped by cross-language information gaps, resulting in inaccurate or incomplete public information.
Language-Agnostic Modeling of Source Reliability on Wikipedia
Researchers developed a language-agnostic machine learning model to assess the reliability of web domains used as references across multiple Wikipedia language editions, evaluating domain credibility within articles on controversial topics such as Climate Change, COVID-19, and Biology.
Who are the “Heroes of CRISPR”? Public science communication on Wikipedia and the challenge of micro-notability
Researchers applied a digital method called Name Edit Analysis to trace how individual scientists are cited within CRISPR-related Wikipedia articles, examining the challenge of 'micro-notability' in public science communication. They found dynamic, ongoing negotiations over which scientists are credited in innovation narratives, revealing that Wikipedia's community-driven editorial process shapes public attribution of scientific discovery.
Foundations and knowledge clusters in TikTok (Douyin) research: evidence from bibliometric and topic modelling analyses
The study provides a comprehensive bibliometric analysis of TikTok research, examining 542 journal articles from the Scopus database. Researchers found that while TikTok research has expanded rapidly, author collaboration networks remain fragmented, and there is limited research cooperation between institutions in developed and developing countries.
Constitutive and Material: An Empirical Analysis of the Two Dimensions of the Communication on Microplastics in Japanese Journals
This study analyzed how microplastic communication has been framed in Japanese academic journals, examining both content and material dimensions of how science about plastic pollution is produced and shared. The research provides insight into how public understanding of microplastics developed in Japan as a scientific and social concern.