Hi all,
The next Research Showcase, with the theme of Images on Wikipedia, will be live-streamed Wednesday, April 19, at 16:30 UTC.
Find your local time here.
You can join the conversation on IRC at #wikimedia-research or on the YouTube chat.
This month's presentations:
- A large scale study of reader interactions with images on Wikipedia
- By Daniele Rama, University of Turin
- Wikipedia is the largest source of free encyclopedic knowledge and one of the most visited sites on the Web. To increase reader understanding of the article, Wikipedia editors add images within the text of the article’s body. However, despite their widespread usage on web platforms and the huge volume of visual content on Wikipedia, little is known about the importance of images in the context of free knowledge environments. To bridge this gap, we collect data about English Wikipedia reader interactions with images during one month and perform the first large-scale analysis of how interactions with images happen on Wikipedia. First, we quantify the overall engagement with images, finding that one in 29 pageviews results in a click on at least one image, one order of magnitude higher than interactions with other types of article content. Second, we study what factors associate with image engagement and observe that clicks on images occur more often in shorter articles and articles about visual arts or transports and biographies of less well-known people. Third, we look at interactions with Wikipedia article previews and find that images help support reader information need when navigating through the site, especially for more popular pages. The findings in this study deepen our understanding of the role of images for free knowledge and provide a guide for Wikipedia editors and web user communities to enrich the world’s largest source of encyclopedic knowledge.
- Visual gender biases in Wikipediaː A systematic evaluation across the ten most spoken languages
- By Pablo Beytia, Catholic University of Chile
- The existing research suggests a significant gender gap in Wikipedia biographical articles, with a minimal representation of women and gender asymmetries in the textual content. However, the visual aspects of this gap (e.g., image volume and quality) have received little attention. This study examined asymmetries between women's and men's biographies, exploring written and visual content across the ten most widely spoken languages. The cross-lingual analysis reveals that (1) the most salient male biases appear when editors select which personalities should have a Wikipedia page, (2) the trends in written and visual content are dissimilar, (3) male biographies tend to have more images across languages, and (4) female biographies have better visual quality on average. The open database of this study provides eight indicators of gender asymmetries in ten occupational domains and ten languages. That information allows for a granular view of gender biases, as well as exploring more macroscopic phenomena, such as the similarity between Wikipedia versions according to their gender bias structures.
- Beytía, P., Agarwal, P., Redi, M., & Singh, V. K. (2022). Visual Gender Biases in Wikipedia: A Systematic Evaluation across the Ten Most Spoken Languages. Proceedings of the International AAAI Conference on Web and Social Media, 16(1), 43-54. https://doi.org/10.1609/icwsm.v16i1.19271
- https://ojs.aaai.org/index.php/ICWSM/article/view/19271
- Beytía, P. & Wagner, C. (2022). Visibility layers: a framework for systematizing the gender gap in Wikipedia content. Internet Policy Review, 11(1). https://doi.org/10.14763/2022.1.1621
- https://policyreview.info/articles/analysis/visibility-layers-framework-systematising-gender-gap-wikipedia-content
Hope you can join us!
Warm regards,
Emily
--
Emily Lescak (she / her)
Senior Research Community Officer
The Wikimedia Foundation