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Science on Wikipedia and the challenge of micro-notability

 By Arno Simons, Wolfgang Kircheis, Marion Schmidt, Martin Potthast, and Benno Stein.

Robert K. Merton, a famous American sociologist, who studied the reward system in science. 

Wikipedia increasingly shapes the public understanding of science. As one of the most visited websites globally, it serves as a go-to resource for millions seeking information on scientific topics. In addition, search engines rely on Wikipedia's comprehensive science content for direct responses, while Large Language Models leverage it as essential training data.

Because of Wikipedia’s central role in today’s knowledge economy, scientists and their institutions are increasingly seeking recognition on the platform. At a time when public recognition is more important to scientists and their careers than ever before, not being mentioned on Wikipedia can be a real issue, given that the platform significantly shapes the public's view of science.

Wikipedians and scientists alike have already recognized the issue of "academic notability", albeit exclusively on article level. In general, on Wikipedia, "notability is a test used by editors to decide whether a given topic warrants its own article". But there is another equally important issue to be addressed: How does Wikipedia decide whether a scientist should be mentioned in an article that is not about them?

We call this the "micro-notability" problem because it applies at the sub-article level. Being mentioned as a relevant actor in an article about a science-related topic, development or innovation matters because it helps to publicly define a scientist's achievement in the first place – often before a biographical article seems appropriate.

In our new paper we explore how Wikipedia addresses this issue of scientific “micro-notability” by studying the evolution of two articles relating to the CRISPR/Cas9 system and its application to genetic engineering

Introducing a digital method called Name Edit Analysis, we trace the mention of CRISPR researchers in these articles as well as the discussions among Wikipedia editors relating to these mentions. Our method combines quantitative and qualitative approaches. It includes:

  • a taxonomy for name edits, 
  • a tool for plotting the addition and removal of names over time alongside overall article growth,
  • a set of indicators to measure, as well as a tool for plotting, the aggregation of name edits along four dimensions (prominence, controversiality, age, and endurance),
  • a tool for creating context tables, which provide an ideal entry point into close reading analysis. 

Studying Wikipedia’s CRISPR articles, we found dynamic negotiations of micro-notability, characterized by back and forth editing of researcher names and sometimes fierce debates on talk pages. Most surprisingly, while Wikipedia has often been likened to science, we spotted a problematic tension between Wikipedia’s principle of safeguarding against self-promotion and the scholarly norm of “due credit.” In one of our qualitative case studies, an editor who identified as a CRISPR researcher and wanted their own contributions to be recognized was accused of self-promotion by other editors in a one-to-many confrontation. 

To reconcile such types of conflicts, we propose that Wikipedians and scientists collaborate to establish specific micro-notability guidelines that acknowledge scientific contributions while preventing excessive self-promotion. Wikipedians should become aware of micro-notability dynamics and reflect their implications also in terms of their own responsibility for recognizing scientific achievements in a fair way.

For more, see the original article: “Who are the ‘Heroes of CRISPR’? Public science communication on Wikipedia and the challenge of micro-notability”.


Arno Simons is a sociologist and philosopher studying how scientists communicate with other scientists as well as with policy makers, journalists, and the wider public. To analyze such communications empirically, Arno combines quantitative and qualitative methods, including large language models, network analysis, and expert interviews. Arno’s research foci include science communication on Wikipedia and in traditional media, expert networks and experimental practices at the science-policy nexus, and biomedical translation.

Wolfgang Kircheis is a linguist and computer scientist studying how science, priority, and innovation can be traced on Wikipedia. Wolfgang has researched the extraction of Wikipedia articles on science and technology as well as references therein and how they can be tracked over the course of articles’ revision histories. His interests include natural language processing, information extraction, and corpus analysis.

Marion Schmidt is a research associate at the DZHW. One focus of her work is investigating the quality of bibliometric data and procedures, another is analyzing how scientific communities deal with misconduct and uncertainty of knowledge claims. She uses mixed-methods approaches that involve bibliometric analysis, quantitative text analysis, and qualitative methods.

Martin Potthast holds the chair of Intelligent Language Technologies at Leipzig University. His research focuses on language technologies, search engines, and the analysis and synthesis of information. Martin contributes to the research areas of information retrieval, natural language processing, and artificial intelligence. Some of his contributions have been awarded scientific prizes.

Benno Stein is professor of Computer Science and heads the “Intelligent Information Systems” group at the Bauhaus University, Weimar. His research deals with theories, algorithms and tools for information retrieval, machine learning, natural language processing, and symbolic knowledge processing. He has been awarded scientific and commercial prizes for several of his research achievements.