Abstract
Opt-in surveys are the most widespread method used to study participation in online communities, but produce biased results in the absence of adjustments for non-response. A 2008 survey conducted by the Wikimedia Foundation and United Nations University at Maastricht is the source of a frequently cited statistic that less than 13% of Wikipedia contributors are female. However, the same study suggested that only 39.9% of Wikipedia readers in the US were female – a finding contradicted by a representative survey of American adults by the Pew Research Center conducted less than two months later. Combining these two datasets through an application and extension of a propensity score estimation technique used to model survey non-response bias, we construct revised estimates, contingent on explicit assumptions, for several of the Wikimedia Foundation and United Nations University at Maastricht claims about Wikipedia editors. We estimate that the proportion of female US adult editors was 27.5% higher than the original study reported (22.7%, versus 17.8%), and that the total proportion of female editors was 26.8% higher (16.1%, versus 12.7%).
Highlights
Describing the demographics of individuals who contribute to Wikipedia, the largest volunteer-written, free knowledge resource on the Internet, as well as other ‘‘peer production’’ communities [1], presents challenges to traditional sampling and survey methods [2]
After applying weights based on the propensity score model reported in Table 1, we estimate that females, married people, and individuals with children were underrepresented in the Wikimedia Foundation (WMF)/
Weighted logistic regression model estimating the likelihood of a US adult Wikipedia reader responding to the WMF/UNU-MERIT survey along a set of covariates shared between the WMF/UNU-MERIT and Pew surveys. age is given in years and all other variables are dummy variables
Summary
Describing the demographics of individuals who contribute to Wikipedia, the largest volunteer-written, free knowledge resource on the Internet, as well as other ‘‘peer production’’ communities [1], presents challenges to traditional sampling and survey methods [2]. One of the most well-known examples of such an opt-in web survey occurred between October 29 and November 3, 2008, when researchers at the Wikimedia Foundation (WMF) and the United Nations University at Maastricht (UNU-MERIT) used a notice on each Wikipedia web page to administer an opt-in survey to 179,192 Wikipedia users and contributors [3]. The WMF/ UNU-MERIT survey’s claim that less than 13% of Wikipedia contributors are female was widely reported in the press and prompted the Wikimedia Foundation to launch an initiative to raise the proportion of female contributors to 25% [4]. The WMF/UNU-MERIT survey relied on a non-random sample of self-selected participants. Self-selection is common to other surveys of Wikipedia contributors, which have shown similar results [5]
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