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For political leanings, the
Facebook Audience API provides five levels: Very Conservative, Conservative, Moderate, Liberal, Very Liberal. To measure the political leaning of an outlet, MBM firstly finds the fraction of readers having different political leanings, and then multiply the fraction for each category with the following values: very liberal (–2), liberal (–1), moderate (0), conservative (1), and very conservative (2). The sum of such scores provides a single polarization score for the outlet, ranging between –2 and 2, where a negative score indicates that a media outlet is read more by a liberal leaning audience, while a positive score indicates a conservative leaning audience. In the original paper, MBM is compared to alternative approaches used to infer the political leanings of news media outlets, finding that this method highly correlates with most alternatives."
471:" we focus on how the editors' attitudes, namely being broad-minded or stubborn, affect the consensus-building process in a model of Knowledge (XXG). We further investigate how banning editors affects the speed with which conflicts or debates can be resolved. For the analysis, we use an agent-based opinion model developed to simulate different aspects of Knowledge (XXG). We show that, in most cases, banning agents from editing an article slows down the consensus-building process, and increases the system’s relaxation time. We show further, and counterintuitively, that with large groups of 'extremists' who hold other than the central opinion, consensus can be reached faster and the article will be less biased."
516:"About a quarter of each Knowledge (XXG) language edition is dedicated to representing 'local content', i.e. the corresponding cultural context —geographical places, historical events, political figures, among others—. To investigate the relevance of such content for users and communities, we present an analysis of reader and editor engagement in terms of pageviews and edits. The results, consistent across fifteen diverse language editions, show that these articles are more engaging for readers and especially for editors. The highest proportion of edits on cultural context content is generated by anonymous users, and also administrators engage proportionally more than plain registered editors "
400:"As a null hypothesis, a knowledge source represents a political constellation in an unbiased way if the relative number of politicians from a given party who are represented as an entity in a knowledge source equals the relative number of this party in a relevant real-life context. consider “having a Knowledge (XXG) page” (etc.) as an important contributor to public visibility of a person and their party. The baseline is then – relatively – easy to define: the shares of the vote or the number of seats of parties Y at times T in a given political body. We started by concentrating on the national parliament, the Chamber of People’s Representatives (
299:, "we cannot see differences among macro topics". This "general trend" was also found for the top 10 (sub-)topic areas and the top 10 Wikiprojects, although with "minor shifts . For example, the topic sports has a higher conservative-leaning fraction of citations, all the while maintaining a liberal-leaning skew. The WikiProjects Politics and India are more liberal-leaning than the average, instead. Taken together, these results confirm that the overall trend towards liberal political polarization is not specific to some areas of Knowledge (XXG), but seems to be widespread across topics and WikiProjects."
547:"This study explores how historical knowledge is produced on Knowledge (XXG). The project is based on multiple methodologies ranging from qualitative analysis of Knowledge (XXG) pages related to history, survey with Knowledge (XXG) editors, to quantitative analysis of participatory practices within the Knowledge (XXG) community. The main argument is that Knowledge (XXG) allows people to discuss the past, express their opinions and emotions about history and its significance in the present and the future through the portal of “talk” that Knowledge (XXG) provides .
575:"Knowledge (XXG)’s capability of producing historical narratives, its self-critical character through the talk pages, and its open character are significant tools that should not be underestimated. The popularity of Knowledge (XXG) and, particularly, the popularity of the historical pages that are visited daily by a lot of people have to be studied and not be neglected as a kind of not “real history.” Knowledge (XXG) cannot change radically the historical scholarship but can bring the historian closer to the society."
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594:"Broken external references on Knowledge (XXG) which lack archived copies are marked as 'permanently dead'. But, we find this term to be a misnomer, as many previously dysfunctional links work fine today. For links which do not work, it is rarely the case that no archived copies exist. Instead, we find that the current policy for determining which archived copies for an URL are not erroneous is too conservative, and many URLs are archived for the first time only after they no longer work."
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319:(but not that site's bias ratings). They note in passing that "that, while there are only 1467 citations rated as 'VERY LOW' , there remains a sizable fraction of citations to low or mixed reliability outlets" on English Knowledge (XXG), as of 2020. (It might have been interesting to conduct the same analysis with the English Knowledge (XXG)'s own reliability ratings that the community has compiled for numerous news sources at
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420:) in the English-language DBpedia, with a trend growing over time. (During these years, the N-VA’s share of the popular vote increased, but the DBpedia growth clearly exceeds the baseline growth.) Different biases seem to occur in the Dutch-language DBpedia: although on the whole comparatively similar to the baseline, this ontology seems to over-represent the main centrist party (
36:
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424:). Wikidata, in contrast, gives a rather accurate picture of party shares in the national parliament. The French-language Walloon parties are (understandably, given the language focus) under-represented in the Dutch-language DBpedia. Both the overrepresentation of rightist and centrist parties in media coverage have been identified in earlier international research "
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and
Wikidata – with respect to their ontological coverage and diversity, and describe implications for the resulting analyses of text corpora. We describe a case study of the relative over- or underrepresentation of Belgian political parties between 1990 and 2020 in the English-language DBpedia, the
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as a kind of gold standard of unbiased language. (Of course, this opened them up to the question whether the spectrum of opinions present among US federal lawmakers is an appropriate baseline for an international encyclopedia, even if their analysis was focused on articles related to US politics.) A
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2/3rds of the
Anglosphere is a majority, but not so much of one that Knowledge (XXG) would be expected to match American biases. Frankly, the premise of the study is that American political biases are some objective standard that Knowledge (XXG) should be trying to emulate. Since that's not and has
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However, in a linear regression analysis (which also takes article topic and WikiProjects into account), the authors "cannot see a clear pattern emerge. While high reliability shows a liberal skew, very high reliability shows a conservative skew in turn. Mixed sources tend to be more liberal, while
274:
To estimate the political polarization of
Knowledge (XXG) citations, we use the Media Bias Monitor. This system collects demographic data about the Facebook followers of 20,448 distinct news media outlets . These data include political leanings, gender, age, income, ethnicity and national identity.
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Our results indicate that consensus is reached extremely slowly if the bias of the article can be changed only by a small amount. To resolve the conflict faster, one must either increase the change of bias in one edit or the ratio of extremists. In general, the latter cannot be controlled
873:
Filipe N Ribeiro, Lucas
Henrique, Fabricio Benevenuto, Abhijnan Chakraborty, Juhi Kulshrestha, Mahmoudreza Babaei, and Krishna P Gummadi. Media bias monitor: Quantifying biases of social media news outlets at large-scale. In Twelfth international AAAI conference on web and social media,
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In
Knowledge (XXG), there is already a method aimed at resolving disputes of that sort. The solution is to move the disputed questions into a new section (or page) where they can be discussed freely. The new trend to move disputed parts of the article into the
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As with research examining other kinds of bias (like gender, language or geography), studying political bias involves the non-trivial problem of defining a "neutral" baseline against which to compare
Knowledge (XXG)'s content. For example, in a series of
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sections is a good way to handle this problem. Assigning arguments and opinions to a small section of the article that is much easier to modify makes the full article less disputed. Thus, tolerance towards the main article increases "
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Motivating their second research question, the authors "speculate that editors may introduce political polarization in their sources in order to prioritise reliable ones" (which might remind one of
Stephen Colbert's dictum
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published on occasion of
Knowledge (XXG)'s 20th anniversary ("Knowledge (XXG), veinte años de conocimiento libre"), which comprises various other research papers, most of which are in Spanish with an English abstract.
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low and very low reliability ones tend to be more conservative." Overall, they conclude that "the case for a possible association between low reliability and conservative news outlets disappear" in the end.
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2017 paper studied both political and gender bias by comparing
Knowledge (XXG)'s coverage of topics to that of "political periodicals geared toward either liberal or conservative ideologies" (e.g.
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200:"Distribution of Knowledge (XXG)’s news media citation political polarization scores using Kernel Density Estimates (KDE). Negative: liberal; positive: conservative." (Figure 2 from the paper)
283:"The average Knowledge (XXG) citation polarization score (red line) is -0.51 (median -0.52) , therefore leaning towards liberal. The bulk of citations also falls between the range -1 and 0."
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never been Knowledge (XXG)'s goal, and given the weirdness of the dataset (Facebook user data and Media Bias Monitor?), it's questionable. Oddly enough, though, Media Bias Monitor itself
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a moderate yet systematic liberal polarization in the selection of news media sources. We also show that this effect is not mitigated by controlling for news media factual reliability."
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Other recent publications that could not be covered in time for this issue include the items listed below. Contributions, whether reviewing or summarizing newly published research,
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Ech. So they compared an international encyclopedia to American publications and claim it's bad we don't perfectly align with them? Most of the Anglosphere is left of America.
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387:"Diversity Searcher is a tool originally developed to help analyse diversity in news media texts We compare two data sources that Diversity Searcher has worked with –
323:– where, ironically, "Media Bias/Fact Check" is itself currently rated as "generally unreliable, as it is self published", somewhat in contrast to the present paper and
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Dutch-language DBpedia, and Wikidata . In particular, we came across a staggering overrepresentation of the political right in the English-language DBpedia."
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extracted in 2020, which the second author and others have already examined from different angles in other research publications (cf. our previous coverage: "
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404:, henceforth KVV) and used the number of seats at the beginning of a legislature. We also looked at the regional (Flemish) parliaments (
306:"Distribution of Knowledge (XXG)’s news media citation reliability scores" according to Media Bias/Fact Check (figure 1 from the paper)
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Simulation of article disputes finds that "it is more important not to have intolerant editors than to have very tolerant ones"
291:"Distribution of Knowledge (XXG) citation political polarization scores for the top 10 WikiProjects" (figure from the paper)
416:"These results not only confirm our first informal observation of over-representation of rightwing parties (especially the
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A monthly overview of recent academic research about Knowledge (XXG) and other Wikimedia projects, also published as the
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522:"The Knowledge (XXG) Diversity Observatory: A Project to Identify and Bridge Content Gaps in Knowledge (XXG)"
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nominations for the "Wikimedia Foundation Research Award of the Year" 2022, to be submitted until February 6.
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English Knowledge (XXG) biased against conservative and female topics, at least when compared to US magazines
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Yeah a bit silly of a story - of course stuff will be more left-leaning, that's most of the academic world
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30 Catholic U.J.L. & Tech. __ (Forthcoming), Santa Clara Univ. Legal Studies Research Paper No. 4277296
479:" for the consensus it is more important not to have intolerant editors than to have very tolerant ones.
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Knowledge (XXG)'s "moderate yet systematic" liberal citation bias: And other new research publications.
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Matching domain names between MBM and the "Knowledge (XXG) Citations" dataset, the study finds that
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Karadeniz, Ozgur; Berendt, Bettina; Kiyak, Sercan; Mertens, Stefan; d'Haenens, Leen (2022-12-29),
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379:"Political representation bias in DBpedia and Wikidata as a challenge for downstream processing"
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with current attempts by Internet regulators to rein in on user-generated content websites and
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709:"Modeling the Knowledge (XXG) to Understand the Dynamics of Long Disputes and Biased Articles"
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Political representation bias in DBpedia and Wikidata as a challenge for downstream processing
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English Knowledge (XXG)'s news citations found to have "moderate yet systematic" liberal bias
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found to be over-eager in declaring links as "permanently dead" but late in archiving them
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A preprint titled "Polarization and reliability of news sources in Knowledge (XXG)" finds
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747:"The Role of Local Content in Knowledge (XXG): A Study on Reader and Editor Engagement"
508:"The Role of Local Content in Knowledge (XXG): A Study on Reader and Editor Engagement"
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This is an earlier paper by the dissertation's author. From the "Conclusion" section:
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More newbies mean more conflict, but extreme tolerance can still achieve eternal peace
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6.7% of Knowledge (XXG) articles cite at least one academic journal article with DOI
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That InternetArchiveBot blurb is quite concerning. Any attempts to fix this issue?
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This dissertation includes detailed examinations of the history of discussions at
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The present study relies on a different source that has since become available:
837:. IMC '22. New York, NY, USA: Association for Computing Machinery. pp. 388–394.
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792:"Discussing the Past: The Production of Historical Knowledge on Knowledge (XXG)"
539:"Discussing the Past: The Production of Historical Knowledge on Knowledge (XXG)"
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See also our review of a related earlier paper involving one of the authors: "
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263:), and women's vs. men's magazines, respectively (see our earlier coverage: "
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Nyayachavadi, Anish; Zhu, Jingyuan; Madhyastha, Harsha V. (2022-10-25).
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Ribé, Marc Miquel; Laniado, David; Kaltenbrunner, Andreas (2021-05-17).
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885:"Customer File Custom Audiences - Meta Marketing API - Documentation"
440:(whom some Wikipedians might recall for his – later retracted – 2005
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Knowledge (XXG)'s "moderate yet systematic" liberal citation bias
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of Knowledge (XXG)'s demise due to volunteer burnout) contrasts
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315:). To test this hypothesis, they use the reliability ratings of
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Polarization and reliability of news sources in Knowledge (XXG)
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831:"Characterizing "permanently dead" links on Knowledge (XXG)"
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Proceedings of the 22nd ACM Internet Measurement Conference
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that (among other results) found Knowledge (XXG) to be
1043:If your comment has not appeared here, you can try
808:"Producing Historical Knowledge on Knowledge (XXG)"
567:"Producing Historical Knowledge on Knowledge (XXG)"
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How Knowledge (XXG) keeps up with COVID-19 research
483:deliberately, but the former can be influenced.
327:that it cites in justification of using MBFC.)
446:Knowledge (XXG)'s "Assume Good Faith" principle
412:From the "Results and interpretation" section:
614:Yang, Puyu; Colavizza, Giovanni (2022-11-21),
553:Talk:Atomic bombings of Hiroshima and Nagasaki
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353:The Wikimedia Foundation's Research team is
350:for videos and slides of past presentations.
244:, Greenstein and Zhu used the United States
1218:Knowledge (XXG) Signpost archives 2023-02
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18:Knowledge (XXG):Knowledge (XXG) Signpost
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313:"Reality has a well-known liberal bias"
238:"more slanted towards Democratic views"
436:In this legal essay, US legal scholar
295:Breaking down polarization ratings by
806:Apostolopoulos, Petros (2019-04-29).
790:Apostolopoulos, Petros (2022-04-28).
226:"A Map of Science in Knowledge (XXG)"
29:
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707:Rudas, Csilla; Török, János (2018).
242:"bias was moving from left to right"
862:Supplementary references and notes:
794:. North Carolina State University.
520:(cf. by some of the same authors:
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402:Kamer van volksvertegenwoordigers
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475:From the "Conclusion" section:
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1039:add the page to your watchlist
240:than Britannica, although its
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325:the peer-reviewed publication
185:Wikimedia Research Newsletter
1153:09:23, 9 February 2023 (UTC)
1137:18:50, 9 February 2023 (UTC)
1129:. Currently celebrating his
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1089:21:10, 7 February 2023 (UTC)
1074:16:23, 7 February 2023 (UTC)
1066:. Currently celebrating his
725:10.12759/hsr.43.2018.1.72-88
667:"Assuming Good Faith Online"
432:"Assuming Good Faith Online"
454:this issue's "In the media"
396:From the "Method" section:
347:Wikimedia Research Showcase
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713:Historical Social Research
812:Madison Historical Review
561:Talk:September 11 attacks
365:Other recent publications
1095:Most of the Anglosphere
297:ORES article topic areas
843:10.1145/3517745.3561451
671:SSRN Electronic Journal
1125:Has about 8.2% of all
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247:Congressional Record
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914:"Recent research" →
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1023:Discuss this story
993:WikiProject report
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906:"Recent research"
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