Hello everyone, This is a friendly reminder that this month's research showcase on *Ensuring Content Integrity on Wikipedia *will be starting in an hour at 9:30 AM PT / 16:30 UTC. *We invite you to watch via the YouTube stream: https://www.youtube.com/live/GgYh6zbrrss <https://www.youtube.com/live/GgYh6zbrrss>.*
Best, Kinneret On Thu, Jun 12, 2025 at 8:12 PM Kinneret Gordon <kgor...@wikimedia.org> wrote: > Hi everyone, > > The June 2025 Research Showcase will be live-streamed next Wednesday, June > 18, at 9:30 AM PT / 16:30 UTC. Find your local time here > <https://zonestamp.toolforge.org/1750264200>. Our theme this month is > *Ensuring > Content Integrity on Wikipedia*. > > *We invite you to watch via the YouTube > stream: https://www.youtube.com/live/GgYh6zbrrss > <https://www.youtube.com/live/GgYh6zbrrss>.* As always, you can join the > conversation in the YouTube chat as soon as the showcase goes live. > > Our presentations this month: > The Differential Effects of Page Protection on Wikipedia Article Quality > By > *Manoel Horta Ribeiro (Princeton University)*Wikipedia strives to be an > open platform where anyone can contribute, but that openness can sometimes > lead to conflicts or coordinated attempts to undermine article quality. To > address this, administrators use “page protection"—a tool that restricts > who can edit certain pages. But does this help the encyclopedia, or does it > do more harm than good? In this talk, I’ll present findings from a > large-scale, quasi-experimental study using over a decade of English > Wikipedia data. We focus on situations where editors requested page > protection and compare the outcomes for articles that were protected versus > similar ones that weren’t. Our results show that page protection has mixed > effects: it tends to benefit high-quality articles by preventing decline, > but it can hinder improvement in lower-quality ones. These insights reveal > how protection shapes Wikipedia content and help inform when it’s most > appropriate to restrict editing, and when it might be better to leave the > page open. > > Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms > By > *Joshua Ashkinaze (University of Michigan)*Large language models (LLMs) > are trained on broad corpora and then used in communities with specialized > norms. Is providing LLMs with community rules enough for models to follow > these norms? We evaluate LLMs' capacity to detect (Task 1) and correct > (Task 2) biased Wikipedia edits according to Wikipedia's Neutral Point of > View (NPOV) policy. LLMs struggled with bias detection, achieving only 64% > accuracy on a balanced dataset. Models exhibited contrasting biases (some > under- and others over-predicted bias), suggesting distinct priors about > neutrality. LLMs performed better at generation, removing 79% of words > removed by Wikipedia editors. However, LLMs made additional changes beyond > Wikipedia editors' simpler neutralizations, resulting in high-recall but > low-precision editing. Interestingly, crowdworkers rated AI rewrites as > more neutral (70%) and fluent (61%) than Wikipedia-editor rewrites. > Qualitative analysis found LLMs sometimes applied NPOV more comprehensively > than Wikipedia editors but often made extraneous non-NPOV-related changes > (such as grammar). LLMs may apply rules in ways that resonate with the > public but diverge from community experts. While potentially effective for > generation, LLMs may reduce editor agency and increase moderation workload > (e.g., verifying additions). Even when rules are easy to articulate, having > LLMs apply them like community members may still be difficult. > > Best, > Kinneret > > -- > > Kinneret Gordon > > Lead Research Community Officer > > Wikimedia Foundation <https://wikimediafoundation.org/> > > *Learn more about Wikimedia Research <https://research.wikimedia.org/>* > _______________________________________________ Wiki-research-l mailing list -- wiki-research-l@lists.wikimedia.org To unsubscribe send an email to wiki-research-l-le...@lists.wikimedia.org
