https://wikipediaquality.com/api.php?action=feedcontributions&user=Darlin&feedformat=atomWikipedia Quality - User contributions [en]2024-03-29T06:55:19ZUser contributionsMediaWiki 1.30.0https://wikipediaquality.com/index.php?title=On_Trusting_Wikipedia&diff=28095On Trusting Wikipedia2021-03-07T15:01:07Z<p>Darlin: cat.</p>
<hr />
<div>{{Infobox work<br />
| title = On Trusting Wikipedia<br />
| date = 2009<br />
| authors = [[P. D. Magnus]]<br />
| doi = 10.3366/E1742360008000555<br />
| link = https://www.cambridge.org/core/journals/episteme/article/on-trusting-wikipedia/A5B4ED5E3B1D6E42CFB0883502973787<br />
}}<br />
'''On Trusting Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2009, written by [[P. D. Magnus]].<br />
<br />
== Overview ==<br />
Given the fact that many people use [[Wikipedia]] , authors should ask: Can authors trust it? The empirical evidence suggests that Wikipedia articles are sometimes quite good but that they vary a great deal. As such, it is wrong to ask for a monolithic verdict on Wikipedia . Interacting with Wikipedia involves assessing where it is likely to be reliable and where not. Author identify five strategies that authors use to assess claims from other sources and argue that, to a greater of lesser degree, Wikipedia frustrates all of them. Interacting responsibly with something like Wikipedia requires new epistemic methods and strategies.<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Magnus, P. D.. (2009). "[[On Trusting Wikipedia]]". Cambridge University Press. DOI: 10.3366/E1742360008000555. <br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Magnus |first1=P. D. |title=On Trusting Wikipedia |date=2009 |doi=10.3366/E1742360008000555 |url=https://wikipediaquality.com/wiki/On_Trusting_Wikipedia |journal=Cambridge University Press}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Magnus, P. D.. (2009). &amp;quot;<a href="https://wikipediaquality.com/wiki/On_Trusting_Wikipedia">On Trusting Wikipedia</a>&amp;quot;. Cambridge University Press. DOI: 10.3366/E1742360008000555. <br />
</nowiki><br />
</code><br />
<br />
<br />
<br />
[[Category:Scientific works]]</div>Darlinhttps://wikipediaquality.com/index.php?title=Cross-Modal_Search_on_Social_Networking_Systems_by_Exploring_Wikipedia_Concepts&diff=28094Cross-Modal Search on Social Networking Systems by Exploring Wikipedia Concepts2021-03-07T14:23:29Z<p>Darlin: Cats.</p>
<hr />
<div>{{Infobox work<br />
| title = Cross-Modal Search on Social Networking Systems by Exploring Wikipedia Concepts<br />
| date = 2016<br />
| authors = [[Wei Wang]]<br />[[Xiaoyan Yang]]<br />[[Shouxu Jiang]]<br />
| doi = 10.1007/978-3-319-49304-6_41<br />
| link = https://link.springer.com/content/pdf/10.1007%2F978-3-319-49304-6_41.pdf<br />
}}<br />
'''Cross-Modal Search on Social Networking Systems by Exploring Wikipedia Concepts''' - scientific work related to [[Wikipedia quality]] published in 2016, written by [[Wei Wang]], [[Xiaoyan Yang]] and [[Shouxu Jiang]].<br />
<br />
== Overview ==<br />
The increasing popularity of [[social network]]ing systems (SNSs) has created large quantities of data from multiple modalities such as text and image. Retrieval of data, however, is constrained to a specific modality. Moreover, text on SNSs is usually short and noisy, and remains active for a (short) period. Such characteristics, conflicting with settings of traditional text search techniques, render them ineffective in SNSs. To alleviate these problems and bridge the gap between searches over different modalities, authors propose a new algorithm that supports cross-modal search about social documents as text and images on SNSs. By exploiting [[Wikipedia]] concepts, text and images are transformed into a set of common concepts, based on which searches are conducted. A new ranking algorithm is designed to rank social documents based on their informativeness and semantic relevance to a query. Authors evaluate ranking algorithm on both [[Twitter]] and [[Facebook]] datasets. The results confirm the effectiveness of approach.<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Wang, Wei; Yang, Xiaoyan; Jiang, Shouxu. (2016). "[[Cross-Modal Search on Social Networking Systems by Exploring Wikipedia Concepts]]". Springer, Cham. DOI: 10.1007/978-3-319-49304-6_41. <br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Wang |first1=Wei |last2=Yang |first2=Xiaoyan |last3=Jiang |first3=Shouxu |title=Cross-Modal Search on Social Networking Systems by Exploring Wikipedia Concepts |date=2016 |doi=10.1007/978-3-319-49304-6_41 |url=https://wikipediaquality.com/wiki/Cross-Modal_Search_on_Social_Networking_Systems_by_Exploring_Wikipedia_Concepts |journal=Springer, Cham}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Wang, Wei; Yang, Xiaoyan; Jiang, Shouxu. (2016). &amp;quot;<a href="https://wikipediaquality.com/wiki/Cross-Modal_Search_on_Social_Networking_Systems_by_Exploring_Wikipedia_Concepts">Cross-Modal Search on Social Networking Systems by Exploring Wikipedia Concepts</a>&amp;quot;. Springer, Cham. DOI: 10.1007/978-3-319-49304-6_41. <br />
</nowiki><br />
</code><br />
<br />
<br />
<br />
[[Category:Scientific works]]<br />
[[Category:Twi Wikipedia]]</div>Darlinhttps://wikipediaquality.com/index.php?title=Trace:_Linguistic-Based_Approach_for_Automatic_Lecture_Video_Segmentation_Leveraging_Wikipedia_Texts&diff=28093Trace: Linguistic-Based Approach for Automatic Lecture Video Segmentation Leveraging Wikipedia Texts2021-03-07T13:55:44Z<p>Darlin: Embed</p>
<hr />
<div>{{Infobox work<br />
| title = Trace: Linguistic-Based Approach for Automatic Lecture Video Segmentation Leveraging Wikipedia Texts<br />
| date = 2015<br />
| authors = [[Rajiv Ratn Shah]]<br />[[Yi Yu]]<br />[[Anwar Dilawar Shaikh]]<br />[[Roger Zimmermann]]<br />
| doi = 10.1109/ISM.2015.18<br />
| link = <br />
}}<br />
'''Trace: Linguistic-Based Approach for Automatic Lecture Video Segmentation Leveraging Wikipedia Texts''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Rajiv Ratn Shah]], [[Yi Yu]], [[Anwar Dilawar Shaikh]] and [[Roger Zimmermann]].<br />
<br />
== Overview ==<br />
In multimedia-based e -- learning systems, the accessibility and searchability of most lecture video content is still insufficient due to the unscripted and spontaneous speech of the speakers. Moreover, this problem becomes even more challenging when the quality of such lecture videos is not sufficiently high. To extract the structural knowledge of a multi-topic lecture video and thus make it easily accessible it is very desirable to divide each video into shorter clips by performing an automatic topic-wise video segmentation. To this end, this paper presents the TRACE system to automatically perform such a segmentation based on a linguistic approach using [[Wikipedia]] texts. TRACE has two main contributions: (i) the extraction of a novel linguistic-based Wikipedia feature to segment lecture videos efficiently, and (ii) the investigation of the late fusion of video segmentation results derived from state-of-the-art algorithms. Specifically for the late fusion, authors combine confidence scores produced by the models constructed from visual, transcriptional, and Wikipedia [[features]]. According to experiments on lecture videos from VideoLectures.NET and NPTEL, the proposed algorithm segments knowledge structures more accurately compared to existing state-of-the-art algorithms. The evaluation results are very encouraging and thus confirm the effectiveness of TRACE.<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Shah, Rajiv Ratn; Yu, Yi; Shaikh, Anwar Dilawar; Zimmermann, Roger. (2015). "[[Trace: Linguistic-Based Approach for Automatic Lecture Video Segmentation Leveraging Wikipedia Texts]]".DOI: 10.1109/ISM.2015.18. <br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Shah |first1=Rajiv Ratn |last2=Yu |first2=Yi |last3=Shaikh |first3=Anwar Dilawar |last4=Zimmermann |first4=Roger |title=Trace: Linguistic-Based Approach for Automatic Lecture Video Segmentation Leveraging Wikipedia Texts |date=2015 |doi=10.1109/ISM.2015.18 |url=https://wikipediaquality.com/wiki/Trace:_Linguistic-Based_Approach_for_Automatic_Lecture_Video_Segmentation_Leveraging_Wikipedia_Texts}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Shah, Rajiv Ratn; Yu, Yi; Shaikh, Anwar Dilawar; Zimmermann, Roger. (2015). &amp;quot;<a href="https://wikipediaquality.com/wiki/Trace:_Linguistic-Based_Approach_for_Automatic_Lecture_Video_Segmentation_Leveraging_Wikipedia_Texts">Trace: Linguistic-Based Approach for Automatic Lecture Video Segmentation Leveraging Wikipedia Texts</a>&amp;quot;.DOI: 10.1109/ISM.2015.18. <br />
</nowiki><br />
</code></div>Darlinhttps://wikipediaquality.com/index.php?title=References:_Cultural_Politics_of_User-Generated_Encyclopaedias:_Comparing_Chinese_Wikipedia_and_Baidu_Baike&diff=28092References: Cultural Politics of User-Generated Encyclopaedias: Comparing Chinese Wikipedia and Baidu Baike2021-03-07T12:50:50Z<p>Darlin: Embed</p>
<hr />
<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 />
<br />
== 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).<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Liao, Han-Teng. (2014). "[[References: Cultural Politics of User-Generated Encyclopaedias: Comparing Chinese Wikipedia and Baidu Baike]]".<br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Liao |first1=Han-Teng |title=References: Cultural Politics of User-Generated Encyclopaedias: Comparing Chinese Wikipedia and Baidu Baike |date=2014 |url=https://wikipediaquality.com/wiki/References:_Cultural_Politics_of_User-Generated_Encyclopaedias:_Comparing_Chinese_Wikipedia_and_Baidu_Baike}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Liao, Han-Teng. (2014). &amp;quot;<a href="https://wikipediaquality.com/wiki/References:_Cultural_Politics_of_User-Generated_Encyclopaedias:_Comparing_Chinese_Wikipedia_and_Baidu_Baike">References: Cultural Politics of User-Generated Encyclopaedias: Comparing Chinese Wikipedia and Baidu Baike</a>&amp;quot;.<br />
</nowiki><br />
</code></div>Darlinhttps://wikipediaquality.com/index.php?title=Graf_Version_of_Catalan_Portions_of_Wikipedia_Corpus&diff=28091Graf Version of Catalan Portions of Wikipedia Corpus2021-03-07T12:37:50Z<p>Darlin: Adding categories</p>
<hr />
<div>{{Infobox work<br />
| title = Graf Version of Catalan Portions of Wikipedia Corpus<br />
| date = 2012<br />
| authors = [[Gemma Boleda]]<br />
| link = https://repositori.upf.edu/handle/10230/20050<br />
}}<br />
'''Graf Version of Catalan Portions of Wikipedia Corpus''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Gemma Boleda]].<br />
<br />
== Overview ==<br />
This is the stand-off GrAF version of Catalan portions of the [[Wikipedia]] (based on a 2006 dump). This Wikipedia Catalan Corpus contains 122052 articles that contain about 47,3 million words in raw text format. It has been cleaned by erasing disambiguation pages, removing some XML tags and homogenizing lists ending tag. Then, the corpus has been processed for adding structural tagging (head, paragraph, sentence, list, etc.) and morphosyntactic information.<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Boleda, Gemma. (2012). "[[Graf Version of Catalan Portions of Wikipedia Corpus]]". Universitat Pompeu Fabra. Institut Universitari de Lingüística Aplicada (IULA). <br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Boleda |first1=Gemma |title=Graf Version of Catalan Portions of Wikipedia Corpus |date=2012 |url=https://wikipediaquality.com/wiki/Graf_Version_of_Catalan_Portions_of_Wikipedia_Corpus |journal=Universitat Pompeu Fabra. Institut Universitari de Lingüística Aplicada (IULA)}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Boleda, Gemma. (2012). &amp;quot;<a href="https://wikipediaquality.com/wiki/Graf_Version_of_Catalan_Portions_of_Wikipedia_Corpus">Graf Version of Catalan Portions of Wikipedia Corpus</a>&amp;quot;. Universitat Pompeu Fabra. Institut Universitari de Lingüística Aplicada (IULA). <br />
</nowiki><br />
</code><br />
<br />
<br />
<br />
[[Category:Scientific works]]<br />
[[Category:Catalan Wikipedia]]</div>Darlinhttps://wikipediaquality.com/index.php?title=Menta:_Inducing_Multilingual_Taxonomies_from_Wikipedia&diff=28090Menta: Inducing Multilingual Taxonomies from Wikipedia2021-03-07T12:34:00Z<p>Darlin: cats.</p>
<hr />
<div>{{Infobox work<br />
| title = Menta: Inducing Multilingual Taxonomies from Wikipedia<br />
| date = 2010<br />
| authors = [[Gerard de Melo]]<br />[[Gerhard Weikum]]<br />
| doi = 10.1145/1871437.1871577<br />
| link = http://dl.acm.org/citation.cfm?id=1871577<br />
| plink = https://www.researchgate.net/profile/Gerard_De_Melo/publication/221614201_MENTA_inducing_multilingual_taxonomies_from_Wikipedia/links/548701750cf268d28f06fd70.pdf<br />
}}<br />
'''Menta: Inducing Multilingual Taxonomies from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2010, written by [[Gerard de Melo]] and [[Gerhard Weikum]].<br />
<br />
== Overview ==<br />
In recent years, a number of projects have turned to [[Wikipedia]] to establish large-scale taxonomies that describe orders of magnitude more entities than traditional manually built knowledge bases. So far, however, the [[multilingual]] nature of Wikipedia has largely been neglected. This paper investigates how entities from all editions of Wikipedia as well as [[WordNet]] can be integrated into a single coherent taxonomic class hierarchy. Authors rely on linking heuristics to discover potential taxonomic relationships, graph partitioning to form consistent equivalence classes of entities, and a Markov chain-based ranking approach to construct the final taxonomy. This results in MENTA (Multilingual Entity Taxonomy), a resource that describes 5.4 million entities and is presumably the largest multilingual lexical knowledge base currently available.<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Melo, Gerard de; Weikum, Gerhard. (2010). "[[Menta: Inducing Multilingual Taxonomies from Wikipedia]]".DOI: 10.1145/1871437.1871577. <br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Melo |first1=Gerard de |last2=Weikum |first2=Gerhard |title=Menta: Inducing Multilingual Taxonomies from Wikipedia |date=2010 |doi=10.1145/1871437.1871577 |url=https://wikipediaquality.com/wiki/Menta:_Inducing_Multilingual_Taxonomies_from_Wikipedia}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Melo, Gerard de; Weikum, Gerhard. (2010). &amp;quot;<a href="https://wikipediaquality.com/wiki/Menta:_Inducing_Multilingual_Taxonomies_from_Wikipedia">Menta: Inducing Multilingual Taxonomies from Wikipedia</a>&amp;quot;.DOI: 10.1145/1871437.1871577. <br />
</nowiki><br />
</code><br />
<br />
<br />
<br />
[[Category:Scientific works]]</div>Darlinhttps://wikipediaquality.com/index.php?title=Policy_and_Participation_on_Social_Media:_the_Cases_of_Youtube,_Facebook,_and_Wikipedia&diff=28089Policy and Participation on Social Media: the Cases of Youtube, Facebook, and Wikipedia2021-03-07T12:32:01Z<p>Darlin: + cat.</p>
<hr />
<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 />
<br />
== 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 />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
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 />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{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 />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
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 />
</nowiki><br />
</code><br />
<br />
<br />
<br />
[[Category:Scientific works]]</div>Darlinhttps://wikipediaquality.com/index.php?title=Qwwwq:_Querying_Wikipedia_Without_Writing_Queries&diff=28088Qwwwq: Querying Wikipedia Without Writing Queries2021-03-07T12:28:59Z<p>Darlin: + Embed</p>
<hr />
<div>{{Infobox work<br />
| title = Qwwwq: Querying Wikipedia Without Writing Queries<br />
| date = 2016<br />
| authors = [[Massimiliano Battan]]<br />[[Marco Ronchetti]]<br />
| doi = 10.1007/978-3-319-38791-8_24<br />
| link = https://link.springer.com/content/pdf/10.1007%2F978-3-319-38791-8_24.pdf<br />
}}<br />
'''Qwwwq: Querying Wikipedia Without Writing Queries''' - scientific work related to [[Wikipedia quality]] published in 2016, written by [[Massimiliano Battan]] and [[Marco Ronchetti]].<br />
<br />
== Overview ==<br />
Wikipedia contains a wealth of data, some of which somes in a structured form. There have been initiatives to extract such structured knowledge, incorporating it in RDF triples. This allows running queries against the body of knowledge. Unfortunately, writing such queries is an unfeasible task for non-technical people, and even those who are familiar with the SPARQL language face the difficulty of not knowing the logical data schema. The problem has been attacked in many ways, mostly by attempting to provide user interfaces which make it possible to graphically navigate the see of RDF triples. Authors present an alternative user interface, which allows users to start from a [[Wikipedia]] page, and to simply express queries by saying “find me something like this, but with these properties having a value in the [A-B] range”.<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Battan, Massimiliano; Ronchetti, Marco. (2016). "[[Qwwwq: Querying Wikipedia Without Writing Queries]]". Springer, Cham. DOI: 10.1007/978-3-319-38791-8_24. <br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Battan |first1=Massimiliano |last2=Ronchetti |first2=Marco |title=Qwwwq: Querying Wikipedia Without Writing Queries |date=2016 |doi=10.1007/978-3-319-38791-8_24 |url=https://wikipediaquality.com/wiki/Qwwwq:_Querying_Wikipedia_Without_Writing_Queries |journal=Springer, Cham}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Battan, Massimiliano; Ronchetti, Marco. (2016). &amp;quot;<a href="https://wikipediaquality.com/wiki/Qwwwq:_Querying_Wikipedia_Without_Writing_Queries">Qwwwq: Querying Wikipedia Without Writing Queries</a>&amp;quot;. Springer, Cham. DOI: 10.1007/978-3-319-38791-8_24. <br />
</nowiki><br />
</code></div>Darlinhttps://wikipediaquality.com/index.php?title=Jointly_They_Edit:_Examining_the_Impact_of_Community_Identification_on_Political_Interaction_in_Wikipedia&diff=28087Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia2021-03-07T12:27:35Z<p>Darlin: + categories</p>
<hr />
<div>{{Infobox work<br />
| title = Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia<br />
| date = 2013<br />
| authors = [[Jessica J. Neff]]<br />[[David Laniado]]<br />[[Karolin Kappler]]<br />[[Yana Volkovich]]<br />[[Pablo Aragón]]<br />[[Andreas Kaltenbrunner]]<br />
| doi = 10.1371/journal.pone.0060584<br />
| link = http://dl.acm.org/citation.cfm?id=1829372.1829425<br />
| plink = https://arxiv.org/abs/1210.6883<br />
}}<br />
'''Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Jessica J. Neff]], [[David Laniado]], [[Karolin Kappler]], [[Yana Volkovich]], [[Pablo Aragón]] and [[Andreas Kaltenbrunner]].<br />
<br />
== Overview ==<br />
Background<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Neff, Jessica J.; Laniado, David; Kappler, Karolin; Volkovich, Yana; Aragón, Pablo; Kaltenbrunner, Andreas. (2013). "[[Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia]]". Public Library of Science. DOI: 10.1371/journal.pone.0060584. <br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Neff |first1=Jessica J. |last2=Laniado |first2=David |last3=Kappler |first3=Karolin |last4=Volkovich |first4=Yana |last5=Aragón |first5=Pablo |last6=Kaltenbrunner |first6=Andreas |title=Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia |date=2013 |doi=10.1371/journal.pone.0060584 |url=https://wikipediaquality.com/wiki/Jointly_They_Edit:_Examining_the_Impact_of_Community_Identification_on_Political_Interaction_in_Wikipedia |journal=Public Library of Science}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Neff, Jessica J.; Laniado, David; Kappler, Karolin; Volkovich, Yana; Aragón, Pablo; Kaltenbrunner, Andreas. (2013). &amp;quot;<a href="https://wikipediaquality.com/wiki/Jointly_They_Edit:_Examining_the_Impact_of_Community_Identification_on_Political_Interaction_in_Wikipedia">Jointly They Edit: Examining the Impact of Community Identification on Political Interaction in Wikipedia</a>&amp;quot;. Public Library of Science. DOI: 10.1371/journal.pone.0060584. <br />
</nowiki><br />
</code><br />
<br />
<br />
<br />
[[Category:Scientific works]]</div>Darlinhttps://wikipediaquality.com/index.php?title=Real-Time_Event-Based_News_Suggestion_for_Wikipedia_Pages_from_News_Streams&diff=28086Real-Time Event-Based News Suggestion for Wikipedia Pages from News Streams2021-03-07T12:26:08Z<p>Darlin: Cats.</p>
<hr />
<div>{{Infobox work<br />
| title = Real-Time Event-Based News Suggestion for Wikipedia Pages from News Streams<br />
| date = 2018<br />
| authors = [[Lijun Lyu]]<br />[[Besnik Fetahu]]<br />
| doi = 10.1145/3184558.3191642<br />
| link = https://dl.acm.org/citation.cfm?doid=3184558.3191642<br />
}}<br />
'''Real-Time Event-Based News Suggestion for Wikipedia Pages from News Streams''' - scientific work related to [[Wikipedia quality]] published in 2018, written by [[Lijun Lyu]] and [[Besnik Fetahu]].<br />
<br />
== Overview ==<br />
Wikipedia is one of the top visited resources on the Web, furthermore, it is used extensively as the main source of information for applications like Web search, question & answering etc. This is mostly attributed to [[Wikipedia]]'s coverage in terms of topics and real-world entities and the fact that Wikipedia articles are constantly updated with new and emerging facts. However, only a small fraction of articles are considered to be of good quality. The large majority of articles are incomplete and have other quality issues. A strong quality indicator is the presence of external references from third-party sources (e.g. news sources) as suggested by the verifiability principle in Wikipedia. Even for the existing references in Wikipedia there is an inherent lag in terms of the publication time of cited resources and the time they are cited in Wikipedia articles. Authors propose a near real-time suggestion of news references for Wikipedia from a daily news stream. Authors model daily news into specific events, spanning from a day up to year. Thus, authors construct an event-chain from which authors determine when the information in an event has converged and consequentially based on a learning-to-rank approach suggest the most authoritative and complete news article to Wikipedia articles involved in a specific event. Authors evaluate news suggestion approach on a set of 41 events extracted from Wikipedia currents event portal, and on new corpus consisting of daily news between the period of 2016-2017 with more than 14 million news articles. Authors are able to suggest news articles to Wikipedia pages with an overall accuracy of MAP=0.77 and with a minimal lag w.r.t the publication time of the news article.<br />
<br />
== Embed ==<br />
=== Wikipedia Quality ===<br />
<code><br />
<nowiki><br />
Lyu, Lijun; Fetahu, Besnik. (2018). "[[Real-Time Event-Based News Suggestion for Wikipedia Pages from News Streams]]". International World Wide Web Conferences Steering Committee. DOI: 10.1145/3184558.3191642. <br />
</nowiki><br />
</code><br />
<br />
=== English Wikipedia ===<br />
<code><br />
<nowiki><br />
{{cite journal |last1=Lyu |first1=Lijun |last2=Fetahu |first2=Besnik |title=Real-Time Event-Based News Suggestion for Wikipedia Pages from News Streams |date=2018 |doi=10.1145/3184558.3191642 |url=https://wikipediaquality.com/wiki/Real-Time_Event-Based_News_Suggestion_for_Wikipedia_Pages_from_News_Streams |journal=International World Wide Web Conferences Steering Committee}}<br />
</nowiki><br />
</code><br />
<br />
=== HTML ===<br />
<code><br />
<nowiki><br />
Lyu, Lijun; Fetahu, Besnik. (2018). &amp;quot;<a href="https://wikipediaquality.com/wiki/Real-Time_Event-Based_News_Suggestion_for_Wikipedia_Pages_from_News_Streams">Real-Time Event-Based News Suggestion for Wikipedia Pages from News Streams</a>&amp;quot;. International World Wide Web Conferences Steering Committee. DOI: 10.1145/3184558.3191642. <br />
</nowiki><br />
</code><br />
<br />
<br />
<br />
[[Category:Scientific works]]</div>Darlinhttps://wikipediaquality.com/index.php?title=The_Anyone-Can-Edit_Syndrome_Intercreation_Stories_of_Three_Featured_Articles_on_Wikipedia&diff=28085The Anyone-Can-Edit Syndrome Intercreation Stories of Three Featured Articles on Wikipedia2021-03-07T12:23:50Z<p>Darlin: Infobox work</p>
<hr />
<div>{{Infobox work<br />
| title = The Anyone-Can-Edit Syndrome Intercreation Stories of Three Featured Articles on Wikipedia<br />
| date = 2014<br />
| authors = [[Maria Mattus]]<br />
| link = http://www.diva-portal.org/smash/record.jsf?pid=diva2:779783<br />
}}<br />
'''The Anyone-Can-Edit Syndrome Intercreation Stories of Three Featured Articles on Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2014, written by [[Maria Mattus]].<br />
<br />
== Overview ==<br />
The user-generated wiki encyclopedia [[Wikipedia]] was launched in January 2001 by Jimmy Wales and Larry Sanger. Wikipedia has become the world’s largest wiki encyclopedia, and behind many of its entries are interesting stories of creation, or rather intercreation, since Wikipedia is produced by a large number of contributors. Using the slogan “the free encyclopedia that anyone can edit” (Wikipedia 2013), Wikipedia invites everyone to participate, but the participants do not necessarily represent all kinds of individuals or interests – there might be an imbalance affecting the content as well as the perspective conveyed. As a phenomenon Wikipedia is quite complex, and can be studied from many different angels, for instance through the articles’ history and the edits to them. This paper is based on a study of [[Featured Articles]] from the Swedish Wikipedia. Three articles, Fri vilja [Free will], Fjall [Fell], and Edgar Allan Poe, are chosen from a list of Featured Articles that belongs to the subject field culture. The articles’ development has been followed from their very first versions in 2003/2004 to edits made at the end of 2012. The aim is to examine the creation, or intercreation, processes of the articles, and the collaborative production. The data come from non-article material such as revision history pages, article material, and some complementary statistics. Principally the study has a qualitative approach, but with some quantitative elements.</div>Darlin