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A monthly overview of recent academic research about Wikipedia and other Wikimedia projects, also published as the Wikimedia Research Newsletter.
The Wikimedia Foundation's Research department announced the launch of the 2026 Wikimedia Research Fund". It funds
Research Proposals (Type 1), Extended Research Proposals (Type 2), and Event and Community-Building Proposals (Type 3). [...] The maximum request is 50,000 USD (Type 1 and 3) and 150,000 USD (Type 2).
Letters of intent for research proposals (Type 1 and 2) are due by January 16, 2026, and full proposals for all three types on April 3, 2026.
See also our related earlier coverage:
Other recent publications that could not be covered in time for this issue include the items listed below. Contributions, whether reviewing or summarizing newly published research, are always welcome.
This paper in the Journal of Information Science (excerpts) considers networks that have "factoids" as nodes, and associations between them as edges, and finds e.g. that "the inclusion of one factoid [on Wikipedia] leads to the inclusion of many other factoids". From the abstract:[1]
"In collaborative environments, the contribution made by each user is perceived to set the stage for the manifestation of more contribution by other users, termed as the phenomenon of triggering. [...] In this work, we analyse the revision history of Wikipedia articles to examine the traces of triggering present in them. We also build and analyse triggering networks for these articles that capture the association among different pieces of the articles. The analysis of the structural properties of these networks provides useful insights on how the existing knowledge leads to the introduction of more knowledge in these articles [...]"
From the "Discussion" section:
"Our analysis on triggering networks of Wikipedia articles not only validates and extends the old classical theories on the phenomenon of existing knowledge triggering the introduction of more knowledge but also provides useful insights pertaining to the evolution of Wikipedia articles. Examining the network structure reveals many properties of the triggering phenomenon. For example, a well-defined community structure clearly endorses that the inclusion of one factoid leads to the inclusion of many other factoids. Moreover, many of the factoids belonging to a subtopic are introduced together. Furthermore, the core-periphery structure and the degree distribution suggest that all the factoids do not have a similar triggering power. Some factoids lead to the introduction of many more factoids and hence are paramount in the article development process than the factoids. The introduction of these factoids in the articles may be considered as milestones in the article evolution process. Overall, the study explains one of the reasons behind collaborative knowledge building being more efficient than individual knowledge building."
See also our coverage of a related earlier publication by the same authors at OpenSym 2018: "'Triggering' article contributions by adding factoids"
From the abstract:[2]
"This study [...] employs a dataset of politicians who ran for local elections in Japan over approximately 20 years and discovers that the creation and revisions of local politicians' pages are associated with socio-economic factors such as the employment ratio by industry and age distribution. We find that the majority of the suppliers of politicians' information are unregistered and primarily interested in politicians' pages compared to registered users. Additional analysis reveals that users who supply information about politicians before and after an election are more active on Wikipedia than the average user. The findings presented imply that the information supply on Wikipedia, which relies on voluntary contributions, may reflect regional socio-economic disparities."
From the abstract:
...
From this conference abstract:[3]
"With over 50 million observations per year, iNaturalist is one of the world's most successful citizen science projects, uniting millions of people worldwide in observing, sharing, and identifying nature [...]. iNaturalist and Wikipedia have much in common: they are both collaborative, large-scale, open infrastructures made by volunteer communities with long-reaching impact on human knowledge. [...] To enable the seamless upload of iNaturalist images to Wikimedia Commons (which in turn enables their reuse on Wikipedia and other Wikimedia projects), this volunteer community has developed a diverse set of open source tools [...]"
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