https://wikipediaquality.com/api.php?action=feedcontributions&user=Andi&feedformat=atomWikipedia Quality - User contributions [en]2024-03-29T13:52:46ZUser contributionsMediaWiki 1.30.0https://wikipediaquality.com/index.php?title=Wikipedia_Usage_Estimates_Prevalence_of_Influenza-Like_Illness_in_Near_Real-Time&diff=27651Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in Near Real-Time2021-02-13T22:12:42Z<p>Andi: Embed for English Wikipedia, HTML</p>
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<div>{{Infobox work<br />
| title = Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in Near Real-Time<br />
| date = 2015<br />
| authors = [[David J McIver]]<br />[[John S. Brownstein]]<br />
| doi = 10.5210/ojphi.v7i1.5705<br />
| link = https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4512362/<br />
}}<br />
'''Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in Near Real-Time''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[David J McIver]] and [[John S. Brownstein]].<br />
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== Overview ==<br />
Wikipedia usage data has been harnessed to estimate the prevalence of influenza-like illness (ILI) in the US population. By observing the number of times certain key [[Wikipedia]] articles are viewed each day, a model was developed that accurately estimated ILI, within 0.27% of official Centers for Disease Control and Prevention data. Additionally, this method was able to accurately determine the week in which ILI peaked 17% more often than [[Google]] Flu Trends. This work demonstrates the power of open, freely available data to aid in disease surveillance.<br />
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McIver, David J; Brownstein, John S.. (2015). "[[Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in Near Real-Time]]". University of Illinois at Chicago Library. DOI: 10.5210/ojphi.v7i1.5705. <br />
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{{cite journal |last1=McIver |first1=David J |last2=Brownstein |first2=John S. |title=Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in Near Real-Time |date=2015 |doi=10.5210/ojphi.v7i1.5705 |url=https://wikipediaquality.com/wiki/Wikipedia_Usage_Estimates_Prevalence_of_Influenza-Like_Illness_in_Near_Real-Time |journal=University of Illinois at Chicago Library}}<br />
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McIver, David J; Brownstein, John S.. (2015). &amp;quot;<a href="https://wikipediaquality.com/wiki/Wikipedia_Usage_Estimates_Prevalence_of_Influenza-Like_Illness_in_Near_Real-Time">Wikipedia Usage Estimates Prevalence of Influenza-Like Illness in Near Real-Time</a>&amp;quot;. University of Illinois at Chicago Library. DOI: 10.5210/ojphi.v7i1.5705. <br />
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</code></div>Andihttps://wikipediaquality.com/index.php?title=The_Hidden_Order_of_Wikipedia&diff=27650The Hidden Order of Wikipedia2021-02-13T22:09:50Z<p>Andi: Adding embed</p>
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<div>{{Infobox work<br />
| title = The Hidden Order of Wikipedia<br />
| date = 2007<br />
| authors = [[Fernanda B. Viégas]]<br />[[Martin Wattenberg]]<br />[[Matthew Mehall McKeon]]<br />
| doi = 10.1007/978-3-540-73257-0_49<br />
| link = http://dl.acm.org/citation.cfm?id=1784297.1784348<br />
}}<br />
'''The Hidden Order of Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2007, written by [[Fernanda B. Viégas]], [[Martin Wattenberg]] and [[Matthew Mehall McKeon]].<br />
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== Overview ==<br />
Authors examine the procedural side of [[Wikipedia]], the well-known internet encyclopedia. Despite the lack of structure in the underlying wiki technology, users abide by hundreds of rules and follow well-defined processes. Authors case study is the Featured Article (FA) process, one of the best established procedures on the site. Authors analyze the FA process through the theoretical framework of commons governance, and demonstrate how this process blends elements of traditional workflow with peer production. Authors conclude that rather than encouraging anarchy, many aspects of wiki technology lend themselves to the collective creation of formalized process and policy.<br />
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Viégas, Fernanda B.; Wattenberg, Martin; McKeon, Matthew Mehall. (2007). "[[The Hidden Order of Wikipedia]]". Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-540-73257-0_49. <br />
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{{cite journal |last1=Viégas |first1=Fernanda B. |last2=Wattenberg |first2=Martin |last3=McKeon |first3=Matthew Mehall |title=The Hidden Order of Wikipedia |date=2007 |doi=10.1007/978-3-540-73257-0_49 |url=https://wikipediaquality.com/wiki/The_Hidden_Order_of_Wikipedia |journal=Springer, Berlin, Heidelberg}}<br />
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Viégas, Fernanda B.; Wattenberg, Martin; McKeon, Matthew Mehall. (2007). &amp;quot;<a href="https://wikipediaquality.com/wiki/The_Hidden_Order_of_Wikipedia">The Hidden Order of Wikipedia</a>&amp;quot;. Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-540-73257-0_49. <br />
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</code></div>Andihttps://wikipediaquality.com/index.php?title=Manypedia:_Comparing_Language_Points_of_View_of_Wikipedia_Communities&diff=27649Manypedia: Comparing Language Points of View of Wikipedia Communities2021-02-13T22:07:51Z<p>Andi: Category</p>
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<div>{{Infobox work<br />
| title = Manypedia: Comparing Language Points of View of Wikipedia Communities<br />
| date = 2013<br />
| authors = [[Paolo Massa]]<br />[[Federico Scrinzi]]<br />
| doi = 10.5210/fm.v18i1.3939<br />
| link = http://firstmonday.org/ojs/index.php/fm/article/view/3939/3382<br />
}}<br />
'''Manypedia: Comparing Language Points of View of Wikipedia Communities''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Paolo Massa]] and [[Federico Scrinzi]].<br />
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== Overview ==<br />
The three million articles of the [[English Wikipedia]] have been written in a collaborative fashion by more than 14 million volunteer editors. In each article, a community of editors strive to reach a [[neutral point of view]], representing all significant views fairly, proportionately, and without biases. However, beside the English one, there are more than 270 editions of [[Wikipedia]] in [[different language]]s and their relatively isolated communities of editors are not forced by the platform to discuss and negotiate their points of view. So the empirical question is: Do communities on different language Wikipedias develop their own diverse Linguistic Points of View (LPOV)? To answer this question authors created and released as [[open source]] Manypedia, a Web tool whose aim is to facilitate cross–cultural analysis of Wikipedia language communities by providing an easy way to compare automatically translated versions of their different representations of the same topic.<br />
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Massa, Paolo; Scrinzi, Federico. (2013). "[[Manypedia: Comparing Language Points of View of Wikipedia Communities]]".DOI: 10.5210/fm.v18i1.3939. <br />
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{{cite journal |last1=Massa |first1=Paolo |last2=Scrinzi |first2=Federico |title=Manypedia: Comparing Language Points of View of Wikipedia Communities |date=2013 |doi=10.5210/fm.v18i1.3939 |url=https://wikipediaquality.com/wiki/Manypedia:_Comparing_Language_Points_of_View_of_Wikipedia_Communities}}<br />
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Massa, Paolo; Scrinzi, Federico. (2013). &amp;quot;<a href="https://wikipediaquality.com/wiki/Manypedia:_Comparing_Language_Points_of_View_of_Wikipedia_Communities">Manypedia: Comparing Language Points of View of Wikipedia Communities</a>&amp;quot;.DOI: 10.5210/fm.v18i1.3939. <br />
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[[Category:Scientific works]]<br />
[[Category:English Wikipedia]]</div>Andihttps://wikipediaquality.com/index.php?title=Gender_Perspective,_Information_Behaviors,_and_Wikipedia&diff=27648Gender Perspective, Information Behaviors, and Wikipedia2021-02-13T22:06:38Z<p>Andi: + Infobox work</p>
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<div>{{Infobox work<br />
| title = Gender Perspective, Information Behaviors, and Wikipedia<br />
| date = 2009<br />
| authors = [[Sook Lim]]<br />[[Nahyun Kwon]]<br />
| doi = 10.1002/meet.2009.1450460343<br />
| link = http://onlinelibrary.wiley.com/doi/10.1002/meet.2009.1450460343/full<br />
}}<br />
'''Gender Perspective, Information Behaviors, and Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2009, written by [[Sook Lim]] and [[Nahyun Kwon]].<br />
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== Overview ==<br />
The purpose of this study is to examine potential differences between the genders amongst college student's information behaviors of [[Wikipedia]] use. Particularly, this study explores the following research questions:</div>Andihttps://wikipediaquality.com/index.php?title=References:_Cultural_Politics_of_User-Generated_Encyclopaedias:_Comparing_Chinese_Wikipedia_and_Baidu_Baike&diff=27647References: Cultural Politics of User-Generated Encyclopaedias: Comparing Chinese Wikipedia and Baidu Baike2021-02-13T22:05:00Z<p>Andi: Infobox work</p>
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<div>{{Infobox work<br />
| title = References: Cultural Politics of User-Generated Encyclopaedias: Comparing Chinese Wikipedia and Baidu Baike<br />
| date = 2014<br />
| authors = [[Han-Teng Liao]]<br />
| link = https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2508933_code931229.pdf?abstractid=2508933&amp;mirid=1&amp;type=2<br />
}}<br />
'''References: Cultural Politics of User-Generated Encyclopaedias: Comparing Chinese Wikipedia and Baidu Baike''' - scientific work related to [[Wikipedia quality]] published in 2014, written by [[Han-Teng Liao]].<br />
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== Overview ==<br />
Abbreviations used for author names below include the following: [[Baidu]] Baike (BB), Baidu Baike contributors (BB contributors:), [[Chinese Wikipedia]] (zhWP), and [[English Wikipedia]] (enWP).</div>Andihttps://wikipediaquality.com/index.php?title=Arabic_Text_Categorization_based_on_Arabic_Wikipedia&diff=27646Arabic Text Categorization based on Arabic Wikipedia2021-02-13T22:02:11Z<p>Andi: Category</p>
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<div>{{Infobox work<br />
| title = Arabic Text Categorization based on Arabic Wikipedia<br />
| date = 2014<br />
| authors = [[Adnan H. Yahya]]<br />[[Ali Salhi]]<br />
| doi = 10.1145/2537129<br />
| link = http://dl.acm.org/citation.cfm?id=2590408.2537129<br />
}}<br />
'''Arabic Text Categorization based on Arabic Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2014, written by [[Adnan H. Yahya]] and [[Ali Salhi]].<br />
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== Overview ==<br />
This article describes an algorithm for categorizing Arabic text, relying on highly categorized corpus-based datasets obtained from the [[Arabic Wikipedia]] by using manual and automated processes to build and customize [[categories]]. The categorization algorithm was built by adopting a simple categorization idea then moving forward to more complex ones. Authors applied tests and filtration criteria to reach the best and most efficient results that algorithm can achieve. The categorization depends on the statistical relations between the input (test) text and the reference (training) data supported by well-defined [[Wikipedia]]-based categories. Authors algorithm supports two levels for categorizing Arabic text; categories are grouped into a hierarchy of main categories and subcategories. This introduces a challenge due to the correlation between certain subcategories and overlap between main categories. Authors argue that algorithm achieved good performance compared to other methods reported in the literature.<br />
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Yahya, Adnan H.; Salhi, Ali. (2014). "[[Arabic Text Categorization based on Arabic Wikipedia]]".DOI: 10.1145/2537129. <br />
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{{cite journal |last1=Yahya |first1=Adnan H. |last2=Salhi |first2=Ali |title=Arabic Text Categorization based on Arabic Wikipedia |date=2014 |doi=10.1145/2537129 |url=https://wikipediaquality.com/wiki/Arabic_Text_Categorization_based_on_Arabic_Wikipedia}}<br />
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Yahya, Adnan H.; Salhi, Ali. (2014). &amp;quot;<a href="https://wikipediaquality.com/wiki/Arabic_Text_Categorization_based_on_Arabic_Wikipedia">Arabic Text Categorization based on Arabic Wikipedia</a>&amp;quot;.DOI: 10.1145/2537129. <br />
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[[Category:Scientific works]]<br />
[[Category:Arabic Wikipedia]]</div>Andihttps://wikipediaquality.com/index.php?title=A_Semantic_Web-Based_Approach_for_Harvesting_Multilingual_Textual_Definitions_from_Wikipedia_to_Support_Icd-11_Revision&diff=27645A Semantic Web-Based Approach for Harvesting Multilingual Textual Definitions from Wikipedia to Support Icd-11 Revision2021-02-13T21:59:38Z<p>Andi: Adding embed</p>
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<div>{{Infobox work<br />
| title = A Semantic Web-Based Approach for Harvesting Multilingual Textual Definitions from Wikipedia to Support Icd-11 Revision<br />
| date = 2013<br />
| authors = [[Guoqian Jiang]]<br />[[Harold R. Solbrig]]<br />[[Christopher G. Chute]]<br />
| link = the <br />
| plink = through <br />
}}<br />
'''A Semantic Web-Based Approach for Harvesting Multilingual Textual Definitions from Wikipedia to Support Icd-11 Revision''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Guoqian Jiang]], [[Harold R. Solbrig]] and [[Christopher G. Chute]].<br />
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== Overview ==<br />
In <br />
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Jiang, Guoqian; Solbrig, Harold R.; Chute, Christopher G.. (2013). "[[A Semantic Web-Based Approach for Harvesting Multilingual Textual Definitions from Wikipedia to Support Icd-11 Revision]]".<br />
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{{cite journal |last1=Jiang |first1=Guoqian |last2=Solbrig |first2=Harold R. |last3=Chute |first3=Christopher G. |title=A Semantic Web-Based Approach for Harvesting Multilingual Textual Definitions from Wikipedia to Support Icd-11 Revision |date=2013 |url=https://wikipediaquality.com/wiki/A_Semantic_Web-Based_Approach_for_Harvesting_Multilingual_Textual_Definitions_from_Wikipedia_to_Support_Icd-11_Revision}}<br />
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Jiang, Guoqian; Solbrig, Harold R.; Chute, Christopher G.. (2013). &amp;quot;<a href="https://wikipediaquality.com/wiki/A_Semantic_Web-Based_Approach_for_Harvesting_Multilingual_Textual_Definitions_from_Wikipedia_to_Support_Icd-11_Revision">A Semantic Web-Based Approach for Harvesting Multilingual Textual Definitions from Wikipedia to Support Icd-11 Revision</a>&amp;quot;.<br />
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</code></div>Andihttps://wikipediaquality.com/index.php?title=Why_We_Should_All_Edit_Wikipedia&diff=27644Why We Should All Edit Wikipedia2021-02-13T21:57:49Z<p>Andi: Adding infobox</p>
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<div>{{Infobox work<br />
| title = Why We Should All Edit Wikipedia<br />
| date = 2011<br />
| authors = [[James Heilman]]<br />
| link = http://ojs.library.ubc.ca/index.php/ubcmj/article/download/2277/2248<br />
}}<br />
'''Why We Should All Edit Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2011, written by [[James Heilman]].<br />
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== Overview ==<br />
Wikipedia, as most are aware, is the free online encyclopedia that covers nearly everything. Almost anyone can edit it, and nearly everybody reads it. As of June 2011, it had over 3.6 million articles in the English language of which approximately 23,000 pertained to the practice of medicine, and 6,700 discussed aspects of pharmacology. The medical pages in a given month receive between 150 and 200 million page views1 while the pharmacology content receives approximately 35 million.2 For the entire encyclopedia, 40,000 people make more than five edits each month,3 though a much smaller number of editors are actively involved with medicine. However, users involved with WikiProject Medicine are a dedicated group of volunteer physicians, students, and non-professionals with the goal of providing people with free access to reliable, understandable, and current health information.4</div>Andihttps://wikipediaquality.com/index.php?title=Do_as_I_Do::_Authorial_Leadership_in_Wikipedia&diff=27643Do as I Do:: Authorial Leadership in Wikipedia2021-02-13T21:55:56Z<p>Andi: + cat.</p>
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<div>{{Infobox work<br />
| title = Do as I Do:: Authorial Leadership in Wikipedia<br />
| date = 2007<br />
| authors = [[Joseph Reagle]]<br />
| doi = 10.1145/1296951.1296967<br />
| link = http://dl.acm.org/citation.cfm?id=1296967<br />
}}<br />
'''Do as I Do:: Authorial Leadership in Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2007, written by [[Joseph Reagle]].<br />
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== Overview ==<br />
In seemingly egalitarian collaborative on-line communities, like [[Wikipedia]], there is often a paradoxical, or perhaps merely playful, use of the title "Benevolent Dictator" for leaders. Author explore discourse around the use of this title so as to address how leadership works in open content communities. Author first review existing literature on "emergent leadership" and then relate excerpts from community discourse on how leadership is understood, performed, and discussed by [[Wikipedians]]. Author conclude by integrating concepts from existing literature and my own findings into a theory of "authorial" leadership.<br />
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Reagle, Joseph. (2007). "[[Do as I Do:: Authorial Leadership in Wikipedia]]".DOI: 10.1145/1296951.1296967. <br />
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{{cite journal |last1=Reagle |first1=Joseph |title=Do as I Do:: Authorial Leadership in Wikipedia |date=2007 |doi=10.1145/1296951.1296967 |url=https://wikipediaquality.com/wiki/Do_as_I_Do::_Authorial_Leadership_in_Wikipedia}}<br />
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Reagle, Joseph. (2007). &amp;quot;<a href="https://wikipediaquality.com/wiki/Do_as_I_Do::_Authorial_Leadership_in_Wikipedia">Do as I Do:: Authorial Leadership in Wikipedia</a>&amp;quot;.DOI: 10.1145/1296951.1296967. <br />
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[[Category:Scientific works]]</div>Andihttps://wikipediaquality.com/index.php?title=The_Role_of_Conflict_in_Determining_Consensus_on_Quality_in_Wikipedia_Articles&diff=27642The Role of Conflict in Determining Consensus on Quality in Wikipedia Articles2021-02-13T21:53:59Z<p>Andi: Embed</p>
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<div>{{Infobox work<br />
| title = The Role of Conflict in Determining Consensus on Quality in Wikipedia Articles<br />
| date = 2013<br />
| authors = [[Kim Osman]]<br />
| doi = 10.1145/2491055.2491067<br />
| link = http://dl.acm.org/citation.cfm?doid=2491055.2491067<br />
}}<br />
'''The Role of Conflict in Determining Consensus on Quality in Wikipedia Articles''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Kim Osman]].<br />
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== Overview ==<br />
This paper presents research that investigated the role of conflict in the editorial process of the online encyclopedia, [[Wikipedia]]. The study used a grounded approach to analyzing 147 conversations about quality from the archived history of the Wikipedia article Australia . It found that conflict in Wikipedia is a generative friction, regulated by references to policy as part of a coordinated effort within the community to improve the quality of articles.<br />
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Osman, Kim. (2013). "[[The Role of Conflict in Determining Consensus on Quality in Wikipedia Articles]]".DOI: 10.1145/2491055.2491067. <br />
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{{cite journal |last1=Osman |first1=Kim |title=The Role of Conflict in Determining Consensus on Quality in Wikipedia Articles |date=2013 |doi=10.1145/2491055.2491067 |url=https://wikipediaquality.com/wiki/The_Role_of_Conflict_in_Determining_Consensus_on_Quality_in_Wikipedia_Articles}}<br />
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Osman, Kim. (2013). &amp;quot;<a href="https://wikipediaquality.com/wiki/The_Role_of_Conflict_in_Determining_Consensus_on_Quality_in_Wikipedia_Articles">The Role of Conflict in Determining Consensus on Quality in Wikipedia Articles</a>&amp;quot;.DOI: 10.1145/2491055.2491067. <br />
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</code></div>Andihttps://wikipediaquality.com/index.php?title=Using_Wikipedia_to_Teach_Information_Literacy&diff=27641Using Wikipedia to Teach Information Literacy2021-02-13T21:51:43Z<p>Andi: Adding embed</p>
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<div>{{Infobox work<br />
| title = Using Wikipedia to Teach Information Literacy<br />
| date = 2008<br />
| authors = [[Eric Jennings]]<br />
| doi = 10.1080/10691310802554895<br />
| link = http://dx.doi.org/10.1080/10691310802554895<br />
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'''Using Wikipedia to Teach Information Literacy''' - scientific work related to [[Wikipedia quality]] published in 2008, written by [[Eric Jennings]].<br />
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== Overview ==<br />
ABSTRACT Today's college student often starts his research by using a search engine. Because of this, [[Wikipedia]] is increasingly becoming the go-to reference resource for the newest generation of students. However, many students do not know about the problems (e.g., vandalism) associated with this tool other than ambiguous warnings from librarians and faculty who say that it should not be used for research. Librarians and faculty should help remove the stigma associated with Wikipedia by embracing this Website and its imperfections as a way to make information literacy instruction valuable for the twenty-first-century student.<br />
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Jennings, Eric. (2008). "[[Using Wikipedia to Teach Information Literacy]]". Taylor & Francis Group. DOI: 10.1080/10691310802554895. <br />
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{{cite journal |last1=Jennings |first1=Eric |title=Using Wikipedia to Teach Information Literacy |date=2008 |doi=10.1080/10691310802554895 |url=https://wikipediaquality.com/wiki/Using_Wikipedia_to_Teach_Information_Literacy |journal=Taylor & Francis Group}}<br />
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Jennings, Eric. (2008). &amp;quot;<a href="https://wikipediaquality.com/wiki/Using_Wikipedia_to_Teach_Information_Literacy">Using Wikipedia to Teach Information Literacy</a>&amp;quot;. Taylor & Francis Group. DOI: 10.1080/10691310802554895. <br />
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</code></div>Andihttps://wikipediaquality.com/index.php?title=Topic_Pages:_Plos_Computational_Biology_Meets_Wikipedia&diff=27640Topic Pages: Plos Computational Biology Meets Wikipedia2021-02-13T21:50:30Z<p>Andi: Adding categories</p>
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<div>{{Infobox work<br />
| title = Topic Pages: Plos Computational Biology Meets Wikipedia<br />
| date = 2012<br />
| authors = [[Daniel Mietchen]]<br />[[Andrew M. Collings]]<br />[[Robert B. Russell]]<br />[[Philip E. Bourne]]<br />[[Philip E. Bourne]]<br />
| doi = 10.1371/journal.pcbi.1002446<br />
| link = http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002446<br />
}}<br />
'''Topic Pages: Plos Computational Biology Meets Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Daniel Mietchen]], [[Andrew M. Collings]], [[Robert B. Russell]], [[Philip E. Bourne]] and [[Philip E. Bourne]].<br />
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== Overview ==<br />
While there has been much debate about the coverage and quality of [[Wikipedia]] (starting with an article in 2005 [1]), there is no doubt about its value (and increasing role) as a reference source and starting point for in-depth research. For example, within the biomedical sciences, there have been recent articles about the accuracy and [[completeness]] of drug information in Wikipedia [2], Wikipedia as a source of information in nursing care [3] and mental disorders [4], and making biological databases available through Wikipedia [5].<br />
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Mietchen, Daniel; Collings, Andrew M.; Russell, Robert B.; Bourne, Philip E.; Bourne, Philip E.. (2012). "[[Topic Pages: Plos Computational Biology Meets Wikipedia]]". Public Library of Science. DOI: 10.1371/journal.pcbi.1002446. <br />
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{{cite journal |last1=Mietchen |first1=Daniel |last2=Collings |first2=Andrew M. |last3=Russell |first3=Robert B. |last4=Bourne |first4=Philip E. |last5=Bourne |first5=Philip E. |title=Topic Pages: Plos Computational Biology Meets Wikipedia |date=2012 |doi=10.1371/journal.pcbi.1002446 |url=https://wikipediaquality.com/wiki/Topic_Pages:_Plos_Computational_Biology_Meets_Wikipedia |journal=Public Library of Science}}<br />
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Mietchen, Daniel; Collings, Andrew M.; Russell, Robert B.; Bourne, Philip E.; Bourne, Philip E.. (2012). &amp;quot;<a href="https://wikipediaquality.com/wiki/Topic_Pages:_Plos_Computational_Biology_Meets_Wikipedia">Topic Pages: Plos Computational Biology Meets Wikipedia</a>&amp;quot;. Public Library of Science. DOI: 10.1371/journal.pcbi.1002446. <br />
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[[Category:Scientific works]]</div>Andihttps://wikipediaquality.com/index.php?title=Pairing_Wikipedia_Articles_Across_Languages&diff=27639Pairing Wikipedia Articles Across Languages2021-02-13T21:48:39Z<p>Andi: Embed</p>
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<div>{{Infobox work<br />
| title = Pairing Wikipedia Articles Across Languages<br />
| date = 2016<br />
| authors = [[Marcus Klang]]<br />[[Pierre Nugues]]<br />
| link = https://lup.lub.lu.se/search/publication/10b176f2-f95c-492c-9cf7-f29c82acee70<br />
}}<br />
'''Pairing Wikipedia Articles Across Languages''' - scientific work related to [[Wikipedia quality]] published in 2016, written by [[Marcus Klang]] and [[Pierre Nugues]].<br />
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== Overview ==<br />
Wikipedia has become a reference knowledge source for scores of NLP applications. One of its invaluable [[features]] lies in its [[multilingual]] nature, where articles on a same entity or concept can have from one to more than 200 different versions. The interlinking of [[language versions]] in [[Wikipedia]] has undergone a major renewal with the advent of [[Wikidata]], a unified scheme to identify entities and their properties using unique numbers. However, as the interlinking is still manuallycarriedoutbythousandsofeditorsacrosstheglobe,errorsmaycreepintheassignment ofentities. Inthispaper,wedescribeanoptimizationtechniquetomatchautomaticallylanguage versions of articles, and hence entities, that is only based on bags of words and anchors. Authors created a dataset of all the articles on persons authors extracted from Wikipedia in six languages: English, French, German, Russian, Spanish, and Swedish. Authors report a correct match of at least 94.3% on each pair. (Less)<br />
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Klang, Marcus; Nugues, Pierre. (2016). "[[Pairing Wikipedia Articles Across Languages]]". The COLING 2016 Organizing Committee. <br />
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{{cite journal |last1=Klang |first1=Marcus |last2=Nugues |first2=Pierre |title=Pairing Wikipedia Articles Across Languages |date=2016 |url=https://wikipediaquality.com/wiki/Pairing_Wikipedia_Articles_Across_Languages |journal=The COLING 2016 Organizing Committee}}<br />
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Klang, Marcus; Nugues, Pierre. (2016). &amp;quot;<a href="https://wikipediaquality.com/wiki/Pairing_Wikipedia_Articles_Across_Languages">Pairing Wikipedia Articles Across Languages</a>&amp;quot;. The COLING 2016 Organizing Committee. <br />
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</code></div>Andihttps://wikipediaquality.com/index.php?title=Policy_and_Participation_on_Social_Media:_the_Cases_of_Youtube,_Facebook,_and_Wikipedia&diff=27638Policy and Participation on Social Media: the Cases of Youtube, Facebook, and Wikipedia2021-02-13T21:45:49Z<p>Andi: + embed code</p>
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<div>{{Infobox work<br />
| title = Policy and Participation on Social Media: the Cases of Youtube, Facebook, and Wikipedia<br />
| date = 2013<br />
| authors = [[Laura Stein]]<br />
| doi = 10.1111/cccr.12026<br />
| link = http://onlinelibrary.wiley.com/doi/10.1111/cccr.12026/abstract<br />
}}<br />
'''Policy and Participation on Social Media: the Cases of Youtube, Facebook, and Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Laura Stein]].<br />
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== Overview ==<br />
This article examines media participation in the domain of user policies. Author adapt Arnstein's typology of participation as a tool for recognizing specific participatory forms and the levels of power they afford. Applying this tool to user policy documents highlights an important dimension of how social media platforms position user participation and the common policy mechanisms structuring and delimiting participation online. While YouTube and [[Facebook]] policies offer minimal participation over site content and governance, [[Wikipedia]] offers maximal participation. Moreover, understanding the terms of participation inscribed in user policies facilitates both more informed choices about user involvement in online platforms and advocacy for more equitable usage terms in policy, law, and practice.<br />
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Stein, Laura. (2013). "[[Policy and Participation on Social Media: the Cases of Youtube, Facebook, and Wikipedia]]". Wiley Subscription Services, Inc.. DOI: 10.1111/cccr.12026. <br />
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{{cite journal |last1=Stein |first1=Laura |title=Policy and Participation on Social Media: the Cases of Youtube, Facebook, and Wikipedia |date=2013 |doi=10.1111/cccr.12026 |url=https://wikipediaquality.com/wiki/Policy_and_Participation_on_Social_Media:_the_Cases_of_Youtube,_Facebook,_and_Wikipedia |journal=Wiley Subscription Services, Inc.}}<br />
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Stein, Laura. (2013). &amp;quot;<a href="https://wikipediaquality.com/wiki/Policy_and_Participation_on_Social_Media:_the_Cases_of_Youtube,_Facebook,_and_Wikipedia">Policy and Participation on Social Media: the Cases of Youtube, Facebook, and Wikipedia</a>&amp;quot;. Wiley Subscription Services, Inc.. DOI: 10.1111/cccr.12026. <br />
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</code></div>Andihttps://wikipediaquality.com/index.php?title=Improving_Retrieval_Performance_with_Wikipedia%27s_Category_Knowledge&diff=27637Improving Retrieval Performance with Wikipedia's Category Knowledge2021-02-13T21:43:33Z<p>Andi: + categories</p>
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<div>{{Infobox work<br />
| title = Improving Retrieval Performance with Wikipedia's Category Knowledge<br />
| date = 2012<br />
| authors = [[Yin Zeng]]<br />[[Wu Lin]]<br />[[Kai Lei]]<br />[[Lian'en Huang]]<br />
| doi = 10.1109/ICCIS.2012.174<br />
| link = http://ieeexplore.ieee.org/document/6299999/<br />
}}<br />
'''Improving Retrieval Performance with Wikipedia's Category Knowledge''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Yin Zeng]], [[Wu Lin]], [[Kai Lei]] and [[Lian'en Huang]].<br />
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== Overview ==<br />
For text search systems, the ambiguity of short queries often leads to poor performance. To solve this problem, relevance feedback via query-expansion is considered as one effective technique. However, many methods of relevance feedback barely use the knowledge of search results and the improvement of effectiveness is limited because the knowledge used is limited. In this paper authors try to include [[Wikipedia]]'s category knowledge to improve the poor retrieval performance. A method of category feedback is proposed, which is based on the information of [[Wikipedia categories]]. Categories instead of terms and documents are provided to users for feedback. Finally, an experimental search system is developed which demonstrates the effectiveness of method.<br />
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Zeng, Yin; Lin, Wu; Lei, Kai; Huang, Lian'en. (2012). "[[Improving Retrieval Performance with Wikipedia's Category Knowledge]]". IEEE Computer Society. DOI: 10.1109/ICCIS.2012.174. <br />
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{{cite journal |last1=Zeng |first1=Yin |last2=Lin |first2=Wu |last3=Lei |first3=Kai |last4=Huang |first4=Lian'en |title=Improving Retrieval Performance with Wikipedia's Category Knowledge |date=2012 |doi=10.1109/ICCIS.2012.174 |url=https://wikipediaquality.com/wiki/Improving_Retrieval_Performance_with_Wikipedia's_Category_Knowledge |journal=IEEE Computer Society}}<br />
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Zeng, Yin; Lin, Wu; Lei, Kai; Huang, Lian'en. (2012). &amp;quot;<a href="https://wikipediaquality.com/wiki/Improving_Retrieval_Performance_with_Wikipedia's_Category_Knowledge">Improving Retrieval Performance with Wikipedia's Category Knowledge</a>&amp;quot;. IEEE Computer Society. DOI: 10.1109/ICCIS.2012.174. <br />
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[[Category:Scientific works]]</div>Andihttps://wikipediaquality.com/index.php?title=Extending_Dbpedia_with_Wikipedia_List_Pages&diff=27636Extending Dbpedia with Wikipedia List Pages2021-02-13T21:42:10Z<p>Andi: cats.</p>
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<div>{{Infobox work<br />
| title = Extending Dbpedia with Wikipedia List Pages<br />
| date = 2013<br />
| authors = [[Heiko Paulheim]]<br />[[Simone Paolo Ponzetto]]<br />
| link = http://ceur-ws.org/Vol-1064/Paulheim_Extending_DBpedia.pdf<br />
}}<br />
'''Extending Dbpedia with Wikipedia List Pages''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Heiko Paulheim]] and [[Simone Paolo Ponzetto]].<br />
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== Overview ==<br />
Thanks to its wide coverage and general-purpose [[ontology]], [[DBpedia]] is a prominent dataset in the Linked Open Data cloud. DBpedia's content is harvested from [[Wikipedia]]'s [[infoboxes]], based on manually created mappings. In this paper, authors explore the use of a promising source of knowledge for extending DBpedia, i.e., Wikipedia's list pages. Authors discuss how a combination of frequent pattern mining and [[natural language processing]] (NLP) methods can be leveraged in order to extend both the DBpedia ontology, as well as the instance information in DBpedia. Authors provide an illustrative example to show the potential impact of approach and discuss its main challenges.<br />
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Paulheim, Heiko; Ponzetto, Simone Paolo. (2013). "[[Extending Dbpedia with Wikipedia List Pages]]". CEUR-WS.org. <br />
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{{cite journal |last1=Paulheim |first1=Heiko |last2=Ponzetto |first2=Simone Paolo |title=Extending Dbpedia with Wikipedia List Pages |date=2013 |url=https://wikipediaquality.com/wiki/Extending_Dbpedia_with_Wikipedia_List_Pages |journal=CEUR-WS.org}}<br />
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Paulheim, Heiko; Ponzetto, Simone Paolo. (2013). &amp;quot;<a href="https://wikipediaquality.com/wiki/Extending_Dbpedia_with_Wikipedia_List_Pages">Extending Dbpedia with Wikipedia List Pages</a>&amp;quot;. CEUR-WS.org. <br />
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[[Category:Scientific works]]</div>Andihttps://wikipediaquality.com/index.php?title=The_Heart_Work_of_Wikipedia:_Gendered,_Emotional_Labor_in_the_World%27s_Largest_Online_Encyclopedia&diff=27635The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia2021-02-13T21:41:05Z<p>Andi: Adding embed</p>
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<div>{{Infobox work<br />
| title = The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia<br />
| date = 2015<br />
| authors = [[Amanda Menking]]<br />[[Ingrid Erickson]]<br />
| doi = 10.1145/2702123.2702514<br />
| link = http://dl.acm.org/citation.cfm?doid=2702123.2702514<br />
}}<br />
'''The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Amanda Menking]] and [[Ingrid Erickson]].<br />
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== Overview ==<br />
This note explores the issue of women's participation in [[Wikipedia]] through the lens of emotional labor. Using a grounded theory approach, authors detail the kinds of tasks women [[Wikipedians]] choose to do and explore why they choose the work they do. Authors also explore the emotional costs of their labor and their strategies for coping. Authors analysis of 20 interviews leads us to posit that the gendered and emotional labor required of many women to participate in Wikipedia's production renders it, problematically, a space of conflicting public and private spheres, motivated by antithetical open and closed values. In addition to other contributions, authors believe this insight sheds light on some of the complex dynamics behind Wikipedia's observed gender gap.<br />
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Menking, Amanda; Erickson, Ingrid. (2015). "[[The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia]]".DOI: 10.1145/2702123.2702514. <br />
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{{cite journal |last1=Menking |first1=Amanda |last2=Erickson |first2=Ingrid |title=The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia |date=2015 |doi=10.1145/2702123.2702514 |url=https://wikipediaquality.com/wiki/The_Heart_Work_of_Wikipedia:_Gendered,_Emotional_Labor_in_the_World's_Largest_Online_Encyclopedia}}<br />
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Menking, Amanda; Erickson, Ingrid. (2015). &amp;quot;<a href="https://wikipediaquality.com/wiki/The_Heart_Work_of_Wikipedia:_Gendered,_Emotional_Labor_in_the_World's_Largest_Online_Encyclopedia">The Heart Work of Wikipedia: Gendered, Emotional Labor in the World's Largest Online Encyclopedia</a>&amp;quot;.DOI: 10.1145/2702123.2702514. <br />
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</code></div>Andihttps://wikipediaquality.com/index.php?title=Named_Entity_Corpus_Construction_Using_Wikipedia_and_Dbpedia_Ontology&diff=27634Named Entity Corpus Construction Using Wikipedia and Dbpedia Ontology2021-02-13T21:39:35Z<p>Andi: infobox</p>
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<div>{{Infobox work<br />
| title = Named Entity Corpus Construction Using Wikipedia and Dbpedia Ontology<br />
| date = 2014<br />
| authors = [[YoungGyun Hahm]]<br />[[Jungyeul Park]]<br />[[Kyungtae Lim]]<br />[[Youngsik Kim]]<br />[[Dosam Hwang]]<br />[[Key-Sun Choi]]<br />
| link = http://www.lrec-conf.org/proceedings/lrec2014/pdf/688_Paper.pdf<br />
}}<br />
'''Named Entity Corpus Construction Using Wikipedia and Dbpedia Ontology''' - scientific work related to [[Wikipedia quality]] published in 2014, written by [[YoungGyun Hahm]], [[Jungyeul Park]], [[Kyungtae Lim]], [[Youngsik Kim]], [[Dosam Hwang]] and [[Key-Sun Choi]].<br />
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== Overview ==<br />
In this paper, authors propose a novel method to automatically build a [[named entity]] corpus based on the [[DBpedia]] [[ontology]]. Since most of [[named entity recognition]] systems require time and effort consuming annotation tasks as training data. Work on NER has thus for been limited on certain languages like English that are resource-abundant in general. As an alternative, authors suggest that the NE corpus generated by proposed method, can be used as training data. Authors approach introduces [[Wikipedia]] as a raw text and uses the DBpedia data set for named entity disambiguation. Authors method is language-independent and easy to be applied to many [[different language]]s where Wikipedia and DBpedia are provided. Throughout the paper, authors demonstrate that NE corpus is of comparable quality even to the manually annotated NE corpus.</div>Andi