RT @JemielniakD
I'm sure many of you have been pondering, during sleepless nights, about using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs. Our article comes to the rescue! @Csisc1994

RT @ReaderMeter
📣 Very excited to announce this new dataset—to our knowledge, one of the largest datasets of software mentions extracted from the scientific literature—to help study the impact of research software (and open source in particular) on science. Check it out! twitter.com/cziscience/status/

"WikiDes: A Wikipedia-Based Dataset for Generating Short Descriptions from Paragraphs" Data and method to generate short descriptions of Wikipedia articles from section text.

(Thang Ta et al, 2022)



"EditEval: An Instruction-Based Benchmark for Text Improvements" (and public leaderboard challenge), with a corpus largely drawn from Wikipedia edits arxiv.org/abs/2209.13331 github.com/facebookresearch/Ed

📢Are you a Wikimedia researcher, or interested in becoming one? is now accepting proposals for the second edition of its Research Fund! You can apply for research funds (USD 2K-50K) until December 16, 2022.

More info at:

"Why People Trust Wikipedia Articles: Credibility Assessment Strategies Used by Readers" a Wikipedia trust taxonomy that describes the mechanisms by which readers assess the credibility of Wikipedia articles.

( Elmimouni et al, 2022)



RT @subhapa
[New paper] "Building a Public Domain Voice Database for Odia" doi.org/10.1145/3487553.352493

Context: I started a project for audio recordings of word pronunciations in Odia. The repository now has ~60,000 pronunciation files in Public Domain (2nd largest among South Asian languages).

"Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipedia" Automatically captioning @Wikipedia images by integrating contextual knowledge, based on the WIT dataset.

(Nguyen et al, 2022)


RT @natematias
Also: how does your knowledge of Wikipedia & online behavior stack up against volunteer editors, foundation staff, & @wikiresearch scientists who support the movement? Read the post and take the quiz to find out!

Many thanks to @TempletonWorld for supporting this game/workshop.

RT @natematias
@wikiresearch @TempletonWorld If you're a researcher and are curious how trivia events can lead to more meaningful science, see this article about collaborative conversations by @adamsethlevine and me


"Towards a Digital Reflexive Sociology: Using Wikipedia's Biographical Repository as a Reflexive Tool"
@Wikipedia as a "mirror" for a science (sociology) to reflect on its history and its gaps.

(Beytía and Müller, 2022)

RT @ptbeytia
Excited about this new article on the usefulness of digital methods for reflecting on the social conditions of scientific thought. We employed @Wikipedia to examine sociology and reveal structures, biases and blind spots.
@wikiresearch @Poetics_Journal

RT @emollick
And, on a related note, to write a paper that can get public, press, and social media notice, you should have:
📊Well-labeled graphics/charts of main findings (not just tables & **)
⚖Clear effect sizes/why does the finding matter?
📄Good abstract with few acronyms
🔓Open access!

RT @frimelle
We study the impact of time and a changing resource on the entity linking task using English Wikipedia. We introduce a resource containing entities and their mentions on English @Wikipedia from 2013 to 2022.

"Accounts that never expire: an exploration into privileged accounts on Wikipedia" aisel.aisnet.org/sais2022/39/
A 2011 English Wikipedia policy change to remove the rights of inactive administrators did not reduce the (already low) frequency of admin accounts being compromised.

"Readability of Wikipedia pages on andrology and gynecology: comparative study" researchgate.net/publication/3 💰

Articles are "difficult to read and best suited for advanced readers, such as college students"; no significant gender disparity in readability

"Augmenting Structure with Text for Improved Graph Learning", PhD Thesis from @tararootcake with many methods to improve graph learning by combining structure and text, using and


RT @opensym
OSS/OpenSym 2022 is pleased to announce that this year distinguished paper award goes to
, Andrea Forte, and Jonathan Morgan for their paper: "Why People Trust Wikipedia Articles: Credibility-Assessment Strategies Used by Readers".


Show older

The original server operated by the Mastodon gGmbH non-profit