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Ideological bias in Wikipedia
[edit]Presence of ideological bias in entries related to politics
[edit]A comprehensive study conducted on ten different versions of Wikipedia revealed that disputes predominantly arise in the category of politics, encompassing politicians, political parties, political movements, and ideologies. These political topics accounted for approximately 25% of the disputes observed across all language versions studied.[1]
A 2012 empirical investigation sampled 28,382 entries related to US politics. The study aimed to assess the degree of bias present in these entries, utilizing a political slant index derived from previous research methods employed to measure bias in newspapers. The political slant index gauges the ideological preference towards either Democratic or Republican political leanings by analyzing the frequency of specific key phrases within the text. Examples of such phrases include 'war in Iraq,' 'civil rights,' 'trade deficit,' 'economic growth,' 'illegal immigration,' and 'border security.' Each term is assigned a political orientation index based on its occurrence frequency in the speeches of Democrats or Republicans during US congressional proceedings. The study's authors concluded that early Wikipedia entries tended to exhibit a democratic political orientation, while more recent entries demonstrated a more balanced viewpoint. Moreover, they observed that once an article was written, subsequent revisions did not significantly alter its overall bias. However, they noted that over time, the inclusion of more recent articles with contrasting viewpoints played a role in rebalancing the average perspectives among the entries.[2]
In a subsequent and more extensive study, the same group of researchers conducted a direct comparison between approximately 4,000 articles related to US politics on Wikipedia and the corresponding articles in Encyclopaedia Britannica, which are authored by experts. Employing similar methods to their previous study, they aimed to evaluate the presence of bias in these entries. The findings revealed that Wikipedia articles exhibited a higher tendency to contain biased opinions compared to Britannica articles. However, this bias effect disappeared when the frequency of political bias indicators was measured per word rather than across the entire text of the entries. It was observed that Wikipedia entries tend to be longer than Britannica's entries, which could contribute to a higher quantitative prevalence of non-neutral contributions. The authors also noted that the frequency of political bias indicators within an entry decreased with multiple revisions. If the articles underwent substantial revisions, the frequency of bias compared to Britannica became statistically insignificant. This suggests that a substantial number of contributions are necessary to significantly reduce bias and approach a state of neutrality.[3]
The aforementioned studies primarily focused on analyzing the presence of bias in Wikipedia based on the content of the articles. However, a more recent study conducted in 2022 specifically examined quotations from journalistic and other media sources that were included within Wikipedia entries on the English edition. The objective was to assess whether there was a prevalence of liberal or conservative sources, which could indicate a potential political bias in the encyclopedia. The study identified a moderate but systematic prevalence of liberal journalistic sources. Furthermore, the analysis revealed no clear correlation between the political leanings of a news source and its reliability, indicating that the moderate prevalence of liberal news sources may not be solely attributed to the quest for source reliabiliy.[4]
In a study published in 2015 focusing on the English edition of Wikipedia, researchers examined whether there was a discrepancy in the removal of positive or negative information in biographies of US senators. To investigate this, the researchers introduced positive and negative facts, sourced from reliable references, into the biographical entries of US senators. Their findings revealed that negative facts were more likely to be removed and were removed at a faster rate compared to positive facts. As a result, the researchers concluded that a significant editorial bias exists in Wikipedia entries related to current US senators. However, when a similar test was conducted on the Wikipedia pages of recently retired and deceased senators, the same discrepancy in the removal of positive and negative facts was not observed. This suggests that the bias identified is specific to the pages of active politicians and does not indicate a systemic issue within Wikipedia. Based on these findings, the authors of the study concluded that information generated through collaborative projects like Wikipedia may be susceptible to an editorial bias that favors politically active individuals.[5]
User collaboration on disputed or distorted content
[edit]In a 2016 study focused on the English-language version of Wikipedia, researchers investigated the behavior of users who contribute to articles, particularly within a subset of articles related to US politics. Building upon the terminology introduced in a previous article from 2012, the authors made several notable discoveries. Firstly, they found that users are slightly inclined to contribute to voices that exhibit an opposing bias to their own, which they referred to as the "attraction of opposites." Additionally, they observed that Wikipedia debates tend to exhibit a prevalence of non-segregated conversations over time, meaning that these discussions involve users with differing opinions rather than being restricted to users with homogeneous opinions (segregated debates). This non-segregated nature of conversations fosters the convergence towards a neutral point of view. Furthermore, the study revealed that a user's degree of bias tends to decrease over time and with experience, particularly among those users involved in editing biased voices. The authors estimated that, on average, Republican biased material takes about a year longer to reach a neutral viewpoint compared to Democratic biased material.[6]
A separate study published in 2019, conducted among American users of the English version, produced similar findings. The study highlighted a significant political orientation bias among users contributing to political topics, with a noteworthy trend: the more edits made to an entry, the more balanced the average political orientation of the contributing users becomes. The study also indicated that the quality of entries, as recognized by the Wikipedia community, improves as the diversity of political orientation among contributors increases. User groups comprised of politically polarized individuals generally produce better articles, on average, compared to groups consisting of highly politically aligned users or even moderates. Surprisingly, positive effects of polarization were observed not only in articles related to politics but also in those concerning social issues and even science. Politically polarized groups engage in frequent disagreements, stimulating focused debates that result in higher quality, more robust, and comprehensive edits. However, it is important to acknowledge that these empirical findings are subject to certain limitations. The groups of contributors to these voices may self-select and form in a non-random manner, which can influence the outcomes and interpretations of the studies.[7][8]
In a 2012 study focusing on edit wars within Wikipedia, it was suggested that consensus can often be reached within a reasonable timeframe, even in controversial articles. The conflicts that tend to prolong these edit wars are primarily driven by the influx of new users. It was observed that most edit wars are carried out by a small number of users who are frequently engaged in conflicts, despite their low overall productivity. In these debates, resolution is often reached not based on the merits of the arguments but rather due to external intervention, exhaustion, or the evident numerical dominance of one group over the other.[9]
Drawing from experimental research findings, Holtz et al. proposed a theoretical model of knowledge production in Wikipedia, employing the concept of "productive friction." This model posits that a certain level of interpretative conflict within a group is necessary for the collective process to generate knowledge. The model draws an analogy to the socio-cognitive conflict model used in psychology to elucidate individual learning. According to this hypothesis, if the tensions or friction within a group are too low, the potential for knowledge construction becomes limited since the existing knowledge is deemed sufficient to address the problem at hand. Conversely, if the friction within a community of contributors becomes excessively high, it can lead to the dismissal of respective ideas or even the division of the group, similar to how an individual may struggle to adapt and learn when confronted with an overwhelming amount of novelty.[10]
Production and use of political content in Wikipedia
[edit]Research studies have delved into the production and utilization of politically relevant content within Wikipedia, aiming to discern behaviors that could serve as indicators of broader public trends, particularly during elections.[11] Scholars have investigated the influence of political news, such as election campaigns, on Wikipedia contributors, noting a stimulation in their engagement with political content. [12]In terms of readership, a study conducted in 2016 examined 14 language versions of Wikipedia in the context of two European elections. The findings suggested that access statistics, measured through pageviews, could be utilized to predict voter turnout and changes in party vote shares. However, these statistics were found to offer limited insight into absolute voting results, focusing more on relative trends.[13]
An additional study conducted in 2013 focused on users who openly declared their support for either the US Democratic or Republican parties. The research indicated that these users tended to contribute more frequently to voices aligning with their own political orientation. However, they did not exhibit polarized editing behavior, as they were not inclined to avoid collaboration with political opponents while also not showing a preference for collaboration exclusively with allies. The authors proposed that the shared identity of being a Wikipedian might outweigh potentially divisive aspects of personal identity, such as political affiliation. This finding distinguishes Wikipedia from other social platforms, like Twitter and blogs, where users often exhibit strong polarization by predominantly interacting with users who share similar political orientations. In contrast, Wikipedia can be characterized as a platform where users display a higher degree of interaction across political orientations, akin to forums and similar platforms.[11]
References
[edit]- ^ Yasseri, Taha; Spoerri, Anselm; Graham, Mark; Kertesz, Janos (2013). "The Most Controversial Topics in Wikipedia: A Multilingual and Geographical Analysis". SSRN Electronic Journal. doi:10.2139/ssrn.2269392. ISSN 1556-5068.
- ^ Greenstein, Shane; Zhu, Feng (2012-05-01). "Is Wikipedia Biased?". American Economic Review. 102 (3): 343–348. doi:10.1257/aer.102.3.343. ISSN 0002-8282.
- ^ Greenstein, Shane; Zhu, Feng (2018-03-03). "Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopedia Britannica and Wikipedia". MIS Quarterly. 42 (3): 945–959. doi:10.25300/misq/2018/14084. ISSN 0276-7783.
- ^ Yang, Puyu; Colavizza, Giovanni (2022-04-25). "A Map of Science in Wikipedia". Companion Proceedings of the Web Conference 2022. New York, NY, USA: ACM. doi:10.1145/3487553.3524925.
- ^ Kalla, Joshua L.; Aronow, Peter M. (2015-09-02). "Editorial Bias in Crowd-Sourced Political Information". PLOS ONE. 10 (9): e0136327. doi:10.1371/journal.pone.0136327. ISSN 1932-6203.
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: CS1 maint: unflagged free DOI (link) - ^ Greenstein, Shane; Gu, Yuan; Zhu, Feng (2017). "Ideological Segregation among Online Collaborators: Evidence from Wikipedians" (PDF). Working Paper 22744. Cambridge, MA: National Bureau of Economic Research.
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(help) - ^ Shi, Feng; Teplitskiy, Misha; Duede, Eamon; Evans, James A. (2019-03-04). "The wisdom of polarized crowds". Nature Human Behaviour. 3 (4): 329–336. doi:10.1038/s41562-019-0541-6. ISSN 2397-3374.
- ^ Yasseri, Taha; Menczer, Filippo (2021). "Can the Wikipedia moderation model rescue the social marketplace of ideas?". ArXiv.
- ^ Yasseri, Taha; Sumi, Robert; Rung, András; Kornai, András; Kertész, János (2012-06-20). "Dynamics of Conflicts in Wikipedia". PLoS ONE. 7 (6): e38869. doi:10.1371/journal.pone.0038869. ISSN 1932-6203.
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: CS1 maint: unflagged free DOI (link) - ^ Holtz, Peter; Kimmerle, Joachim; Cress, Ulrike (2018-10-23). "Using big data techniques for measuring productive friction in mass collaboration online environments". International Journal of Computer-Supported Collaborative Learning. 13 (4): 439–456. doi:10.1007/s11412-018-9285-y. ISSN 1556-1607.
- ^ a b Neff, Jessica J.; Laniado, David; Kappler, Karolin E.; Volkovich, Yana; Aragón, Pablo; Kaltenbrunner, Andreas (2013-04-03). "Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia". PLoS ONE. 8 (4): e60584. doi:10.1371/journal.pone.0060584. ISSN 1932-6203.
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: CS1 maint: unflagged free DOI (link) - ^ Keegan, Brian (2018-06-15). "The Dynamics of Peer-Produced Political Information During the 2016 U.S. Presidential Campaign". Proceedings of the International AAAI Conference on Web and Social Media. 12 (1). doi:10.1609/icwsm.v12i1.15043. ISSN 2334-0770.
- ^ Yasseri, Taha; Bright, Jonathan (2016-06-18). "Wikipedia traffic data and electoral prediction: towards theoretically informed models". EPJ Data Science. 5 (1). doi:10.1140/epjds/s13688-016-0083-3. ISSN 2193-1127.