Wikipedia:Wikipedia Signpost/2014-01-29/Recent research
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A monthly overview of recent academic research about Wikipedia and other Wikimedia projects, also published as the Wikimedia Research Newsletter.
In a new paper titled "Bots, bespoke code, and the materiality of software platforms"[1] published in Information, Communication & Society, Stuart Geiger (User:Staeiou) presents a critical reflection on the common view of online communities as sovereign platforms governed by code using Wikipedia as an example. He borrows the term "bespoke" to refer to code that affects the social dynamics of a community, but is designed and owned separately from the software platform (e.g. Wikipedia bots). Geiger mixes vignettes describing his personal experience running en:User:AfDStatBot with discussions of the related literature (including Lessig's famous "code is law") to advocate "examining online communities as both governed by stock and bespoke code, or else we will miss important characteristics of mediated interaction."
- "Precise and Efficient Attribution of Authorship of Revisioned Content": Using a graph-theoretic approach, Flöck and Acosta investigate[2] a new algorithm that can detect the author of a part of document that has been edited by many. They use a units-of-discourse model, to identify paragraph, sentences and words, and their connections. The authors claim that this approach can identify an author with 95% precision, which is more than the current state-of-the art. Most intriguing is that in order to make this comparison they have created the first "gold standard", a hand-made benchmark of 240 Wikipedia pages and their complex authorship histories.
- "Which News Organizations Influence Wikipedia?": This is the question asked in a blog post[3] by a post-doc research scholar at Columbia University's Tow Center for digital journalism. Looking at the top 10 news stories of 2013 - an admittedly subjective set determined by the author - the organizations from which the citations come are analyzed. Leading pack are the New York Times, Washington Post and CNN , but the author notes that the tail of the distribution is very long - 68% of citations are not produced by the top 10 organizations. Qualitative analysis discusses "the surprise for the news organizations that don’t make the top ten; CBS News, ABC News, FOX News [...] this top ten strikes as leaning left overall".
References
- ^ Geiger, R. Stuart. "Bots, bespoke code, and the materiality of software platforms". Information, Communication & Society: 1–15. doi:10.1080/1369118X.2013.873069. ISSN 1369-118X. , author's copy at http://stuartgeiger.com/bespoke-code-ics.pdf
- ^ Fabian Flöck, Maribel Acosta: WikiWho: Precise and Efficient Attribution of Authorship of Revisioned Content. http://www.aifb.kit.edu/web/Inproceedings3398
- ^ Fergus Pitt: Which News Organizations Influence Wikipedia? January 17, 2014, http://towcenter.org/blog/which-news-organizations-influence-wikipedia/
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