A large scale study of reader interactions with images on Wikipedia

@article{Rama2022ALS,
  title={A large scale study of reader interactions with images on Wikipedia},
  author={Daniel S{\'a}nchez Rama and Tiziano Piccardi and Miriam Redi and Rossano Schifanella},
  journal={EPJ Data Science},
  year={2022},
  volume={11},
  pages={1-29}
}
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… 
Going Down the Rabbit Hole: Characterizing the Long Tail of Wikipedia Reading Sessions
TLDR
It is found that article layout influences the structure of rabbit hole sessions and that the fraction of rabbit Hole sessions is higher during the night, and readers are more likely to fall into a rabbit hole starting from articles about entertainment, sports, politics, and history.

References

SHOWING 1-10 OF 67 REFERENCES
Quantifying Engagement with Citations on Wikipedia
TLDR
This work built client-side instrumentation for logging all interactions with links leading from English Wikipedia articles to cited references during one month, and conducted the first analysis of readers’ interactions with citations, finding that overall engagement with citations is low and that references are consulted more commonly when Wikipedia itself does not contain the information sought by the user.
Why We Read Wikipedia
TLDR
These findings advance the understanding of reader motivations and behavior on Wikipedia and can have implications for developers aiming to improve Wikipedia's user experience, editors striving to cater to their readers' needs, third-party services providing access to Wikipedia content, and researchers aiming to build tools such as recommendation engines.
Reader preferences and behavior on Wikipedia
TLDR
It is shown that the most read articles do not necessarily correspond to those frequently edited, suggesting some degree of non-alignment between user reading preferences and author editing preferences.
On the Value of Wikipedia as a Gateway to the Web
TLDR
A detailed analysis of usage logs gathered from Wikipedia users’ client devices sheds light on Wikipedia’s role not only as an important source of information, but also as a high-traffic gateway to the broader Web ecosystem.
Why the World Reads Wikipedia: Beyond English Speakers
TLDR
A large-scale survey of Wikipedia readers across 14 language editions with a log-based analysis of user activity advances understanding of reader motivations and behaviors across Wikipedia languages and has implications for Wikipedia editors and developers of Wikipedia and other Web technologies.
The Visual Side of Wikipedia
  • F. Viégas
  • Art
    2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)
  • 2007
TLDR
A survey conducted with image contributors to Wikipedia reveals key differences in collaborating around images as opposed to text and reveals the potential and some of the limitations of wikis in the realm of visual collaboration.
Image-based information: paintings in Wikipedia
TLDR
The authors conclude that images of paintings are highly valuable information sources, also beyond an art-related context, and that Wikipedia is an important dissemination channel for museum collections.
A Large-scale Study of Wikipedia Users' Quality of Experience
TLDR
A large-scale study of one of the most popular websites, Wikipedia, explicitly asking users for feedback on the browsing experience, leveraging user survey responses to build a data-driven model of user satisfaction which is still far from achieving accurate results.
The_Tower_of_Babel.jpg: Diversity of Visual Encyclopedic Knowledge Across Wikipedia Language Editions
TLDR
The diversity of visual encyclopedic knowledge across 25 language editions of Wikipedia is assessed and the similarities and differences in visual encyclopedia knowledge across language editions are measured.
Faces engage us: photos with faces attract more likes and comments on Instagram
TLDR
The first results on how photos with human faces relate to engagement on large scale image sharing communities are presented, finding that the number of faces, their age and gender do not have an effect.
...
1
2
3
4
5
...