Wikipedia:Wikipedia Signpost/2023-04-03/Recent research

A monthly overview of recent academic research about Wikipedia and other Wikimedia projects, also published as the Wikimedia Research Newsletter.

This arXiv preprint (which according to the authors grew out of a student project for a course titled "Critical Thinking in Data Science" at Harvard University) finds that

Regarding Wikipedia, the authors note it "is an encyclopedia that provides summaries of knowledge and is written from a neutral point of view", concluding that

While the authors employ some quantitative methods to study the bias on the other three sites (particularly Google), the Wikipedia part of the paper is almost entirely qualitative in nature. It focuses on an in-depth comparison of a small set of (quite apparently non-randomly chosen) article topics across languages, not unlike various earlier studies of language bias on Wikipedia (e.g. on the coverage of the Holocaust in different languages, see our previous coverage here and here). Unfortunately, the paper fails to cite such such earlier research (which has also included quantitative results, such as those represented in the "Wikipedia Diversity Observatory", which among other things includes data on topic coverage across 300+ Wikipedia languages) – despite asserting "there has been a lack of investigation into language bias on platforms such as Google, ChatGPT, Wikipedia, and YouTube".

The first and largest part of the paper's examination of Wikipedia's coverage concerns articles about Buddhism and various subtopics, in the English, French, German, Vietnamese, Chinese, Thai, and Nepali Wikipedias. The authors indicate that they chose this topic starting out from the observation that

Somewhat in confirmation of this hypothesis, they find that

However, the authors also observe that "randomness is involved to some degree in terms of topic coverage on Wikipedia", defying overly simplistic predictions of biases based on intellectual traditions. E.g.

A second, shorter section focuses on comparing Wikipedia articles on liberalism and Marxism across languages. Among other things, it observes that the "English article has a long section on Keynesian economics", likely due to its prominent role in the New Deal reforms in the US in the 1930s. In contrast,

Among other proposals for reducing language bias on the four sites, the paper proposes that

Returning to their title metaphor, the authors give Wikipedia credit for at least "show[ing] a rough silhouette of the elephant", whereas e.g. Google only "presents a piece of the elephant based on a user's query language". However, this "silhouette – topic coverage – differs by language. [Wikipedia] writes in a descriptive tone and contextualizes first-person narratives and subjective opinions as cultural, historical, or religious phenomena." YouTube, on the other hand, "displays the 'color' and 'texture' of the elephant as it incorporates images and sounds that are effective in invoking emotions." But its top-rated videos "tend to create a more profound ethnocentric experience as they zoom into a highly confined range of topics or views that conform to the majority's interests".

The papers singles out the new AI-based chatbots as particularly problematic regarding language bias:

On the other hand, the paper's examination of the biases of "ChatGPT-Bing" [sic] highlights among other concerns its reliance on Wikipedia among the sources it cites in its output:

• See the page of the monthly Wikimedia Research Showcase for videos and slides of past presentations.

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.

From the abstract:

From the abstract:

From the abstract:

From the abstract:

Among other examples given in the paper, a Wikidata statement involving the items and properties Q217760, P54, Q221525 and P580 is mapped to the Wikipedia sentence "On 30 January 2010, Wiltord signed with Metz until the end of the season."

Judging from the paper's citations, the authors appear to have been unaware of the Abstract Wikipedia project, which is pursuing a closely related effort.

From the paper: