Wikipedia bias
218523099
The Positioning Matters: Estimating Geographical Bias in the Multilingual Record of Biographies on Wikipedia
This article proposes that an appropriate assessment of the geographical bias in multilingual Wikipedia's content should consider not only the number of articles linked to places, but also their internal positioning i.e. their location in different languages and their centrality in the network of references between articles This idea is studied empirically, systematically evaluating the geographic concentration in the biographical coverage of globally recognized individuals (those whose biographies are found in more than 25 language versions of Wikipedia) Considering the internal positioning levels of these biographies, only 5 countries account for more than 62% of Wikipedia's biographical coverage. In turn, the inequality in coverage between countries reaches very high levels, estimated with a Gini coefficient of .84 and a Palma ratio of 207. In all the tests carried out, the inclusion of the linguistic and/or relational positioning of the articles increases the estimate of inequality in biographical coverage. This suggests that previous estimates of geographical bias, which do not consider differences in internal positioning, have underestimated the degree of inequality in the distribution of information.
WWW
Pablo Beytia
227240954
The Gender Bias Tug of War in a Co creation Community: Core Periphery Tension on Wikipedia
ABSTRACT Commitment to a neutral point of view is a pillar of Wikipedia culture. Despite a strong culture, the open nature of the community presents challenges for cultural assimilation. Central contributors who make up the community's core engage in activism to combat traditional forms of bias. However, peripheral contributors may not adopt or adhere to the community's cultural values and may reflect the very bias the community attempts to combat. These differences create tensions between central and peripheral contributors. Peripheral contributors are likely to contribute traditional types of information bias (e.g. bias against women) In response, central contributors may overcorrect in ways that reverse traditional biases. We compare gender bias on female and male CEO profiles and find evidence of bias that advantages women and disadvantages men. While peripheral contributors may dominate early in the life cycle of core periphery structured open collaboration communities due to the volume of contributions the core dominates in the long term through sustained, systematic activism. Our results suggest that a balance of activity from central and peripheral contributors results in content with the most neutral point of view.
J. Manag. Inf. Syst.
Amber Grace Young Ariel D Wigdor Gerald C Kane
218783922
Linguistic evidence of in group bias in English and Spanish Wikipedia articles about international conflicts
Abstract The aim of this study is to identify linguistic categories which could be bias indicators in both English and Spanish versions of Wikipedia articles about international conflicts. In this sense, Appraisal analysis particularly, engagement is used to examine whether the articles are biased in favor of a group (in group bias) In the present study, only two kinds of these resources are focused: attribution and counter. The hypothesis we are discussing is that, in these articles, engagement categories serve as linguistic indicators of in group bias. The analysis shows important associations between engagement resources and in group bias. The findings seem to confirm that bias is usually expressed implicitly rather than explicitly.
Guadalupe Alvarez Aileen Oeberst Ulrike Cress Laura Ferrari
226283827
Is Wikipedia succeeding in reducing gender bias? Assessing changes in gender bias in Wikipedia using word embeddings
Large text corpora used for creating word embeddings (vectors which represent word meanings) often contain stereotypical gender biases. As a result, such unwanted biases will typically also be present in word embeddings derived from such corpora and downstream applications in the field of natural language processing (NLP) To minimize the effect of gender bias in these settings, more insight is needed when it comes to where and how biases manifest themselves in the text corpora employed. This paper contributes by showing how gender bias in word embeddings from Wikipedia has developed over time. Quantifying the gender bias over time shows that art related words have become more female biased. Family and science words have stereotypical biases towards respectively female and male words. These biases seem to have decreased since 2006, but these changes are not more extreme than those seen in random sets of words. Career related words are more strongly associated with male than with female, this difference has only become smaller in recently written articles. These developments provide additional understanding of what can be done to make Wikipedia more gender neutral and how important time of writing can be when considering biases in word embeddings trained from Wikipedia or from other text corpora.
NLPCSS
Katja Geertruida Schmahl Tom J Viering Stavros Makrodimitris Arman Naseri Jahfari David M J Tax Marco Loog
220546136
Wikipedia's Network Bias on Controversial Topics
The most important feature of Wikipedia is the presence of hyperlinks in pages. Link placement is the product of people's collaboration, consequently Wikipedia naturally inherits human bias. Due to the high influence that links' disposition has on users' navigation sessions, one needs to verify that, given a controversial topic, the hyperlinks' network does not expose users to only one side of the subject. A Wikipedia's topic induced network that prevents users the discovery of different facets of an issue, suffers from structural bias. In this work, we define the static structural bias, which indicates if the strength of connections between pages of contrasting inclinations is the same, and the dynamic structural bias, which quantifies the network's level bias that users face over the course of their navigation sessions. Our measurements of structural bias on several controversial topics demonstrate its existence, revealing that users have low likelihood of reaching pages of opposing inclination from where they start, and that they navigate Wikipedia showing a behaviour much more biased than the expected from the baselines. Our findings advance the relevance of the problem and pave the way for developing systems that automatically measure and propose hyperlink locations that minimize the presence and effects of structural bias.
ArXiv
Cristina Menghini Aris Anagnostopoulos Eli Upfal
226082094
James P. Adams Library: Changing Implicit Bias on Wikipedia: Wikipedia for Educators
A guide to getting started on Wikipedia and exploring ways find, observe, bring attention to, and change implicit bias on Wikipedia.
Janaya Kizzie
226055549
James P. Adams Library: Changing Implicit Bias on Wikipedia: Articles for Deletion Monitoring
A guide to getting started on Wikipedia and exploring ways find, observe, bring attention to, and change implicit bias on Wikipedia.
Janaya Kizzie
226111672
James P. Adams Library: Changing Implicit Bias on Wikipedia: Standards and Rules
A guide to getting started on Wikipedia and exploring ways find, observe, bring attention to, and change implicit bias on Wikipedia.
Janaya Kizzie
226112619
James P. Adams Library: Changing Implicit Bias on Wikipedia: WikiProjects and Groups
A guide to getting started on Wikipedia and exploring ways find, observe, bring attention to, and change implicit bias on Wikipedia.
Janaya Kizzie
226096783
James P. Adams Library: Changing Implicit Bias on Wikipedia: Home
A guide to getting started on Wikipedia and exploring ways find, observe, bring attention to, and change implicit bias on Wikipedia.
Janaya Kizzie