Article feedback pilot goes live

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As recently announced on the tech blog and in the Signpost, we’re launching an experimental new tool today to capture article feedback from readers as part of the Public Policy Initiative. We’re also inviting the user community to help determine its future by joining a workgroup tasked with evaluating it.
The “Article Feedback Tool” allows any reader to quickly and easily assess the sourcing, completeness, neutrality, and readability of a Wikipedia article on a five-point scale. It will be one of several tools used by the Public Policy Initiative to assess the quality of articles. We also hope it will be a way to increase reader engagement by seeking feedback from them on how they view the article, and where it needs improvement.
The tool is currently enabled on about 400 articles related to US public policy. You can see it in action at the bottom of articles such as United States Constitution, Don’t ask, don’t tell or Brown v. Board of Education.
Another goal of this pilot is to try and find a way to collaborate with the community to build tools and features. As main users of the software, Wikimedians are in a unique position to evaluate how a feature performs, and what its strengths and limitations are. The Article Feedback Tool is still very much in a prototype state; we’re hoping the user community can help us determine whether resources should be allocated to improve it (and if so, how), or if it doesn’t meet the users’ needs and should be shelved or completely rethought.
More information about the tool is available on our Questions & Answers page.
If you want to try the tool to assess an article, pick a subject you’re familiar with from the full list and rate it! If you’d like to participate in the evaluation of the tool itself and what becomes of it, please join the workgroup. If you’re interested in article assessment in general, please also join the Public Policy Initiative’s Assessment Team.
Thank you,
Guillaume Paumier,
on behalf of the Features Engineering team

Archive notice: This is an archived post from, which operated under different editorial and content guidelines than Diff.

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