Academic studies about Wikipedia

For a listing about this subject, see Wikipedia:Academic studies of Wikipedia.

In recent years there have been numerous academic studies about Wikipedia in peer-reviewed publications. This research can be grouped into two categories. The first analyzed the production and reliability of the encyclopedia content, while the second investigated social aspects, such as usage and administration. Such studies are greatly facilitated by the fact that Wikipedia's database can be downloaded without needing to ask for the assistance of the site owner.

Content

Production

A minority of editors produce the majority of persistent content

In a landmark peer-reviewed paper, also mentioned in The Guardian, a team of six researchers from the University of Minnesota measured the relationship between editors' edit count and the editors' ability to convey their writings to Wikipedia readers, measured in terms of persistent word views (PWV)—the number of times a word introduced by an edit is viewed. The accounting method is best described using the author's own words: "each time an article is viewed, each of its words is also viewed. When a word written by editor X is viewed, he or she is credited with one PWV." The number of times an article was viewed was estimated from the web server logs.

The researchers analyzed 25 trillion PWVs attributable to registered users in the interval September 1, 2002 − October 31, 2006. At the end of this period, the top 10% of editors (by edit count) were credited with 86% of PWVs, the top 1% about 70%, and the top 0.1% (4200 users) were attributed 44% of PWVs, i.e. nearly half of Wikipedia's "value" as measured in this study. The top 10 editors (by PWV) contributed only 2.6% of PWVs, and only three of them were in top 50 by edit count. From the data, the study authors derived the following relationship:

Growth of PWV share increases super-exponentially by edit count rank; in other words, elite editors (those who edit the most times) account for more value than they would [be attributed] given a power-law relationship.

The study also analyzed the impact of bots on content. By edit count, bots dominate Wikipedia; 9 of the top 10 and 20 of the top 50 are bots. In contrast, in the PWV ranking only two bots appear in the top 50, and none in the top 10.

Based on the steady growth of the influence on those top 0.1% editors by PWV, the study concluded unequivocally:

[...] Frequent editors dominate what people see when they visit Wikipedia and [...] this domination is increasing.

Work distribution and social strata

Further information: Criticism of Wikipedia#Social stratification

A peer-reviewed paper noted the "social stratification in the Wikipedia society" due to the "admins class". The paper suggested that such stratification could be beneficial in some respects but recognized a "clear subsequent shift in power among levels of stratification" due to the "status and power differentials" between administrators and other editors.

Analyzing the entire edit history of Wikipedia up to July 2006, the same study determined that the influence of administrator edits on contents has steadily diminished since 2003, when administrators performed roughly 50% of total edits, to 2006 when only 10% of the edits were performed by administrators. This happened despite the fact that the average number of edits per administrator had increased more than fivefold during the same period. This phenomenon was labeled the "rise of the crowd" by the authors of the paper. An analysis that used as metric the number of words edited instead of the number of edit actions showed a similar pattern. Because the admin class is somewhat arbitrary with respect to the number of edits, the study also considered a breakdown of users in categories based on the number of edits performed. The results for "elite users", i.e. users with more than 10,000 edits, were somewhat in line with those obtained for administrators, except that "the number of words changed by elite users has kept up with the changes made by novice users, even though the number of edits made by novice users has grown proportionally faster". The elite users were attributed about 30% of the changes for 2006. The study concludes:

Thus though their influence may have waned in recent years, elite users appear to continue to contribute a sizeable portion of the work done in Wikipedia. Furthermore, [...] edits made by elite users appear to be substantial in nature. [...]

Reliability

Main article: Reliability of Wikipedia

Jean Goodwin has assessed whether trust in Wikipedia is based on epistemic or pragmatic merits. While readers may not assess the actual knowledge and expertise of the authors of a given article, they may assess the contributors' passion for the project, and communicative design through which that passion is made manifest, and provide a reason for trust.

Geography

Template:See also

Wikipedia articles cover about half a million places on Earth. However, research conducted by the Oxford Internet Institute has shown that the geographic distribution of articles is highly uneven. Most articles are written about North America, Europe, and East Asia, with very little coverage of large parts of the developing world, including most of Africa.

Natural language processing

The textual content and the structured hierarchy of Wikipedia has become an important knowledge source for researchers in natural language processing and artificial intelligence. In 2007 researchers at Technion - Israel Institute of Technology developed a technique called Explicit Semantic Analysis which uses the world knowledge contained in Wikipedia articles. Conceptual representations of words and texts are created automatically and used to compute the similarity between words and texts.

Researchers at Ubiquitous Knowledge Processing Lab use the linguistic and world knowledge encoded in Wikipedia and Wiktionary to automatically create linguistic knowledge bases which are similar to expert-built resources like WordNet. Strube and Ponzetto created an algorithm to identify relationships among words by traversing Wikipedia via its categorization scheme, and concluded that Wikipedia had created "a taxonomy able to compete with WordNet on linguistic processing tasks."

Critiques of content fields

Health information

Main article: Health information on Wikipedia

Health information on Wikipedia is popularly accessed as results from search engines and Search engine result page, which frequently deliver links to Wikipedia articles. Independent assessments of the quality of health information provided on Wikipedia and of who is accessing the information have been undertaken. The number and demographics of people who seek health information on Wikipedia, the scope of health information on Wikipedia, and the quality of the information on Wikipedia have been studied. There are drawbacks to using Wikipedia as a source of health information.

Social aspects

Demographics

A 2007 study by Hitwise, reproduced in Time magazine, found that visitors to Wikipedia are almost equally split 50/50 male/female, but that 60% of edits are made by male editors.

WikiWarMonitor which is part of the European Commission, CORDIS FP7 FET-Open supported project called ICTeCollective, have published:

in 2011 in IEEE Xplore "Edit wars in Wikipedia" for IEEE Third International Conference on Social Computing (SocialCom).

In 2012 in PLoS ONE, it reported that based on circadian activity pattern analysis, the shares of contributions to English Wikipedia, from North America and Europe are almost equal, whereas this increases to 75% of European contributions for the Simple English Wikipedia. The research also covers some other demographic analysis on the other editions in different languages.

In 2013 in Physical Review Letters "Opinions, Conflicts, and Consensus: Modeling Social Dynamics in a Collaborative Environment".

In 2014 published as a book "The Most Controversial Topics in Wikipedia: A Multilingual and Geographical Analysis"; analysed the volume of editing of articles in various language versions of Wikipedia in order to establish the most controversial topics in different languages and groups of languages. For the English version, the top three most controversial articles were George W. Bush, Anarchism and Muhammad. Topics in other languages causing most controversy were Croatia (German), Ségolène Royal (French), Chile (Spanish) and Homosexuality (Czech).

Policies and guidelines

A descriptive study that analyzed English language Wikipedia's policies and guidelines up to September 2007 identified a number of key statistics:

• 44 official policies
• 248 guidelines

Even a short policy like "ignore all rules" was found to have generated a lot of discussion and clarifications:

While the "Ignore all rules" policy itself is only sixteen words long, the page explaining what the policy means contains over 500 words, refers readers to seven other documents, has generated over 8,000 words of discussion, and has been changed over 100 times in less than a year.

The study sampled the expansion of some key policies since their inception:

• Wikipedia:Ignore all rules: 3600% (including the additional document explaining it)
• Wikipedia:Consensus: 1557%
• Wikipedia:Copyrights: 938%
• Wikipedia:What Wikipedia is not: 929%
• Wikipedia:Deletion policy: 580%
• Wikipedia:Civility: 124%

The number for "deletion" was considered inconclusive however because the policy was split in several sub-policies.

Power plays

Template:See also

A 2007 joint peer-reviewed study conducted by researchers from the University of Washington and HP Labs examined how policies are employed and how contributors work towards consensus by quantitatively analyzing a sample of active talk pages. Using a November 2006 database dump, the study focused on 250 talk pages in the tail of the distribution: 0.3% of all talk pages, but containing 28.4% of all talk page revisions, and more significantly, containing 51.1% of all links to policies. From the sampled pages' histories, the study examined only the months with high activity, called critical sections—sets of consecutive months where both article and talk page revisions were significant in number.

The study defined and calculated a measure of policy prevalence. A critical section was considered policy-laden if its policy factor was at least twice the average. Articles were tagged with 3 indicator variables:

• controversial
• featured
• policy-laden

All possible levels of these three factors yielded 8 sampling categories. The study intended to analyze 9 critical sections from each sampling category, but only 69 critical sections could be selected because only 6 articles (histories) were simultaneously featured, controversial, and policy laden.

The study found that policies were by no means consistently applied. Illustrative of its broader findings, the report presented the following two extracts from Wikipedia talk in obvious contrast:

• a discussion where participants decided that calculating a mean from data provided by a government agency constituted original research:

Template:Quotation

• a discussion where logical deduction was used as counterargument for the original research policy:

Template:Quotation

Claiming that such ambiguities easily give rise to power plays, the study identified, using the methods of grounded theory (Strauss), 7 types of power plays:

• article scope (what is off-topic in an article)
• prior consensus (past decisions presented as absolute and uncontested)
• power of interpretation (a sub-community claiming greater interpretive authority than another)
• legitimacy of contributor (his/her expertise)
• threat of sanction (blocking etc.)
• practice on other pages (other pages being considered models to follow)
• legitimacy of source (authority of references being disputed)

Due to lack of space, the study detailed only the first 4 types of power plays that were exercised by merely interpreting policy. A fifth power play category was analyzed; it consisted of blatant violations of policy that were forgiven because the contributor was valued for his contributions despite his lack of respect for rules.

Article scope

The study considers that Wikipedia's policies are ambiguous on scoping issues. The following vignette is used to illustrate the claim:

Template:Quotation

The study gives the following interpretation for the heated debate:

Such struggles over article scope take place even in a hyper-linked environment because the title of an article matters. The “paleocentrism” article is more prestigious and also more likely to be encountered by a reader than an article entitled “the social effect of paleocentrism.”

Prior consensus

The study remarks that in Wikipedia consensus is never final, and what constitutes consensus can change at any time. The study finds that this temporal ambiguity is fertile ground for power plays, and places the generational struggle over consensus in larger picture of the struggle for article ownership:

In practice, [...] there are often de facto owners of pages or coalitions of contributors that determine article content. Prior consensus within this group can be presented as incontestable, masking the power plays that may have gone into establishing a consensus. [...] At issue is the legitimacy of prior consensus. Longtime contributors do not want to waste time having arguments

about issues that they consider to be solved. Pointing to prior consensus, just like linking to policies, provides a method for dealing with trollish behavior. On the other hand, newcomers or fringe contributors often feel that their perspectives

were not represented in prior arguments and want to raise the issue again.

The study uses the following discussion snippet to illustrate this continuous struggle:

Template:Quotation

Power of interpretation

A vignette illustrated how administrators overrode consensus and deleted personal accounts of user/patients suffering from an anonimized illness (named Frupism in the study). The administrator's intervention happened as the article was being nominated to become as a featured article.

Legitimacy of contributor

This type of power play is illustrated by a contributor (U24) that draws on his past contributions to argue against another contributor who is accusing U24 of being unproductive and disruptive:

Template:Quotation

Explicit vie for ownership

The study finds that there are contributors who consistently and successfully violate policy without sanction:

U24 makes several blatant "us or them" vies for power: if U25's actions persist, he will leave. [...] Such actions clearly violate policies against article ownership, civility toward other contributors, and treatment of newcomers. As a newcomer, U25 may not know of these policies, but U26 certainly does. The willing blindness [of U26] stems from the fact that U24 is a valued contributor to philosophy articles and is not bashful about pointing this out. There is a scarcity of contributors with the commitment to consistently produce high-quality content; the Wikipedian community is willing to tolerate abuse and policy violations if valued work is being done.

[...]

Template:Quotation

Obtaining administratorship

Template:See also

Researchers from Carnegie Mellon University devised a probit model of editors who have successfully passed the peer review process to become admins. Using only Wikipedia metadata, including the text of edit summaries, their model is 74.8% accurate in predicting successful candidates.

The paper observed that despite protestations to the contrary, "in many ways election to admin is a promotion, distinguishing an elite core group from the large mass of editors." Consequently, the paper used policy capture – a method that compares nominally important attributes to those that actually lead to promotion in a work environment.

The overall success rate for promotion was 53%, dropping from 75% in 2005 to 42% in 2006 and 2007. This sudden increase in failure rate was attributed to a higher standard that recently promoted administrators had to meet, and supported by anecdotal evidence from another recent study quoting some early admins who have expressed doubt that they would pass muster if their election (RfA) were held recently. In light of these developments the study argued that:

The process once called "no big deal" by the founder of Wikipedia has become a fairly big deal.

Significant factors affecting RfA outcome, numbers in parentheses are not statistically significant at p<.05:

Factor	2006–2007	pre–2006
number of previous RfA attempts	-14.7%	-11.1%
months since first edit	0.4%	(0.2%)
every 1000 article edits	1.8%	(1.1%)
every 1000 Wikipedia policy edits	19.6%	(0.4%)
every 1000 WikiProject edits	17.1%	(7.2%)
every 1000 article talk edits	6.3%	15.4%
each Arb/mediation/wikiquette edit	-0.1%	-0.2%
diversity score (see text)	2.8%	3.7%
minor edits percentage	0.2%	0.2%
edit summaries percentage	0.5%	0.4%
"thanks" in edit summaries	0.3%	(0.0%)
"POV" in edit summaries	0.1%	(0.0%)
Admin attention/noticeboard edits	-0.1%	(0.2%)

Contrary to expectations perhaps, "running" for administrator multiple times is detrimental to the candidate's chance of success. Each subsequent attempt has a 14.8% lower chance of success than the previous one. Length of participation in the project makes only a small contribution to the chance of a successful RfA.

Another significant finding of the paper is that one Wikipedia policy edit or WikiProject edit is worth ten article edits. A related observation is that candidates with experience in multiple areas of the site stood better chance of election. This was measured by the diversity score, a simple count of the number of areas that the editor has participated in. The paper divided Wikipedia in 16 areas: article, article talk, articles/categories/templates for deletion (XfD), (un)deletion review, etc. (see paper for full list). For instance, a user who has edited articles, her own user page, and posted once at (un)deletion review would have a diversity score of 3. Making a single edit in any additional region of Wikipedia correlated with a 2.8% increased likelihood of success in gaining administratorship.

Making minor edits also helped, although the study authors consider that this may be so because minor edits correlate with experience. In contrast, each edit to an Arbitration or Mediation committee page, or a Wikiquette notice, all of which are venues for dispute resolution, decreases the likelihood of success by 0.1%. Posting messages to administrator noticeboards (ANI) had a similarly deleterious effect. The study interpreted this as evidence that editors involved in escalating or protracted conflicts lower their chances of becoming administrators.

Saying "thanks" or variations thereof in edit summaries, and pointing out point of view ("POV") issues (also only in edit summaries because the study only analyzed metadata) were of minor benefit, contributing to 0.3% and 0.1% to candidate's chances in 2006–2007, but did not reach statistical significance before.

A few factors that were found to be irrelevant or marginal at best:

• Editing user pages (including one's own) does not help. Somewhat surprisingly, user talk page edits also do not affect the likelihood of administratorship.
• Welcoming newcomers or saying "please" in edit summaries had no effect.
• Participating in consensus-building, such as RfA votes or the village pump, does not increase the likelihood of becoming admin. The study admits however that participation in consensus was measured quantitatively but not qualitatively.
• Vandal-fighting as measured by the number of edits to the vandalism noticeboard had no effect. Every thousand edits containing variations of "revert" was positively correlated (7%) with adminship for 2006–2007, but did not attain statistical significance unless one is willing to lower the threshold to p<.1). More confusingly, before 2006 the number of reverts was negatively correlated (-6.8%) with adminship success, against without attaining statistical significance even at p<.1. This may be because of the introduction of a policy known as 3RR in 2006 to reduce reverts.

The study suggests that some of the 25% unexplained variability in outcomes may be due to factors that were not measured, such as quality of edits or participation in off-site coordination, such as the (explicitly cited) secret mailing list reported in The Register. The paper concludes:

Merely performing a lot of production work is insufficient for “promotion” in Wikipedia. Candidates’ article edits were weak predictors of success. They also have to demonstrate more managerial behavior. Diverse experience and contributions to the development of policies and WikiProjects were stronger predictors of RfA success. This is consistent with the findings that Wikipedia is a bureaucracy and that coordination work has increased substantially. [...] Participation in Wikipedia policy and WikiProjects was not predictive of adminship prior to 2006, suggesting the community as a whole is beginning to prioritize policymaking and organization experience over simple article-level coordination.

Subsequent research by another group probed the sensemaking activities of individuals during their contributions to RfA decisions. This work establishes that decisions about RfA candidates is based on a shared interpretation of evidence in the wiki and histories of prior interactions.

Machine learning

Automated semantic knowledge extraction using machine learning algorithms is used to "extract machine-processable information at a relatively low complexity cost". DBpedia uses structured content extracted from infoboxes by machine learning algorithms to create a resource of linked data in a Semantic Web.

Wikipedia view statistics and movie revenue

In a study published in PLoS ONE researchers from Oxford Internet Institute and Central European University have shown that the page view statistics of articles about movies are well correlated with the box office revenue of them. They developed a mathematical model to predict the box office takings by analysing the page view counts as well as number of edits and unique editors of the Wikipedia pages on movies. In a related work published in Scientific Reports in 2013, Helen Susannah Moat, Tobias Preis and colleagues demonstrated a link between changes in the number of views of Wikipedia articles relating to financial topics and subsequent large stock market moves.

See also

• Wikipedia:Academic studies of Wikipedia
• Wikipedia:Wikipedia as an academic source
• Wikipedia:Wikipedia in research
• Wikimedia Research Index

Further reading

• Adler, B. T., & L. de Alfaro (2007). "A content-driven reputation system for the wikipedia." Proceedings of the 16th international conference on World Wide Web, doi:10.1145/1242572.1242608
• Amichai; Hamburger, Y.; Lamdan, N.; Madiel, R.; Hayat, T. (2008). "Personality characteristics of Wikipedia members". Cyberpsychology & Behavior. 11 (6): 679–681. doi:10.1089/cpb.2007.0225.
• Blumenstock, J. E. (2008). "Size matters: word count as a measure of quality on Wikipedia." Proceeding of the 17th international conference on World Wide Web, doi doi:10.1145/1367497.1367673
• Bryant, S. L., A. Forte, & A. Bruckman (2005). "Becoming Wikipedian: transformation of participation in a collaborative online encyclopedia." Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work, doi:10.1145/1099203.1099205
• Hu, M., E. P. Lim, A. Sun, H. W. Lauw, & B.-Q. Vuong (2007). "Measuring article quality in wikipedia: models and evaluation." Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, doi:10.1145/1321440.1321476
• Jensen, Richard. "Military History on the Electronic Frontier: Wikipedia Fights the War of 1812," The Journal of Military History 76#4 (October 2012): 523-556; online version
• Kuznetsov, S. (2006). "Motivations of contributors to Wikipedia." ACM SIGCAS Computers and Society, doi:10.1145/1215942.1215943
• Luyt, B., T. C. H. Aaron, L. H. Thian, & C. K. Hong (2007). "Improving Wikipedia's accuracy: Is edit age a solution?" Journal of the American Society for Information Science and Technology, doi:10.1002/asi.v59:2
• Medelyan, O., C. Legg, D. Milne, & I. H. Witten (2008). "Mining meaning from Wikipedia." arXiv, http://arxiv.org/abs/0809.4530
• Park, Taemin Kim (2011) "The visibility of Wikipedia in scholarly publications" First Monday, Volume 16, Number 8, 1 August 2011 http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/viewArticle/3492/3031
• Shachaf, P (2009). "The paradox of expertise: Is the Wikipedia reference desk as good as your library?". Journal of Documentation. 65 (6): 977–996. doi:10.1108/00220410910998951.
• Shachaf, P.; Hara, N. (2010). "Beyond vandalism: Wikipedia trolls". Journal of Information Science. 36 (3): 357–370. doi:10.1177/0165551510365390.
• Stein, K., & C. Hess (2007). "Does it matter who contributes: a study on featured articles in the German Wikipedia." Proceedings of the eighteenth conference on Hypertext and hypermedia, http://doi.acm.org/10.1145/1286240.1286290
• Suh, Bongwon; Chi, Ed H.; Kittur, Aniket; and Pendleton, Bryan A., Bongwon; Chi, Ed H.; Kittur, Aniket; Pendleton, Bryan A. (2008). "Lifting the veil: improving accountability and social transparency in Wikipedia with wikidashboard". Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems. Association for Computing Machinery: 1037. doi:10.1145/1357054.1357214. ISBN 978-1-60558-011-1.{{cite journal}}: CS1 maint: multiple names: authors list (link)
• Urdaneta, G.; Pierre, G.; van Steen, M. (2009). "Wikipedia Workload Analysis for Decentralized Hosting". Elsevier Computer Networks. 53 (11): 1830–1845. doi:10.1016/j.comnet.2009.02.019.
• Vuong, B.-Q., E. P. Lim, A. Sun, M.-T. Le, & H. W. Lauw (2008). "On ranking controversies in Wikipedia: models and evaluation." Proceedings of the international conference on Web search and web data mining, http://doi.acm.org/10.1145/1341531.1341556

External links

• WikiPapers – a compilation of resources (conference papers, journal articles, theses, books, datasets and tools) focused on the research of wikis and Wikipedia