An Analysis of Wikipedia References Across PLOS Publications
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Modeling Popularity and Reliability of Sources in Multilingual Wikipedia
information Article Modeling Popularity and Reliability of Sources in Multilingual Wikipedia Włodzimierz Lewoniewski * , Krzysztof W˛ecel and Witold Abramowicz Department of Information Systems, Pozna´nUniversity of Economics and Business, 61-875 Pozna´n,Poland; [email protected] (K.W.); [email protected] (W.A.) * Correspondence: [email protected] Received: 31 March 2020; Accepted: 7 May 2020; Published: 13 May 2020 Abstract: One of the most important factors impacting quality of content in Wikipedia is presence of reliable sources. By following references, readers can verify facts or find more details about described topic. A Wikipedia article can be edited independently in any of over 300 languages, even by anonymous users, therefore information about the same topic may be inconsistent. This also applies to use of references in different language versions of a particular article, so the same statement can have different sources. In this paper we analyzed over 40 million articles from the 55 most developed language versions of Wikipedia to extract information about over 200 million references and find the most popular and reliable sources. We presented 10 models for the assessment of the popularity and reliability of the sources based on analysis of meta information about the references in Wikipedia articles, page views and authors of the articles. Using DBpedia and Wikidata we automatically identified the alignment of the sources to a specific domain. Additionally, we analyzed the changes of popularity and reliability in time and identified growth leaders in each of the considered months. The results can be used for quality improvements of the content in different languages versions of Wikipedia. -
Wikipedia As a Lens for Studying the Real-Time Formation of Collective Memories of Revolutions
International Journal of Communication 5 (2011), Feature 1313–1332 1932–8036/2011FEA1313 WikiRevolutions: Wikipedia as a Lens for Studying the Real-time Formation of Collective Memories of Revolutions MICHELA FERRON University of Trento PAOLO MASSA Fondazione Bruno Kessler In this article, we propose to interpret the online encyclopedia Wikipedia as an online setting in which collective memories about controversial and traumatic events are built in a collaborative way. We present the richness of data available on the phenomenon, providing examples of users’ participation in the creation of articles related to the 2011 Egyptian revolution. Finally, we propose possible research directions for the empirical study of collective memory formation of traumatic and controversial events in large populations as they unfold over time. Introduction On December 17, 2010, Mohammed Bouazizi, a 26-year-old fruit vendor in the central town of Sidi Bouzid doused himself and set himself on fire in front of a local municipal office. On January 25, 2011, a series of protests began in downtown Cairo and across the country against the government of Egyptian President Hosni Mubarak, in what has been called the “Day of Revolt.” In the following days, protests spread across Tunisia and Egypt, leading to the flight of the Tunisian president Zine El Abidine Ben Ali from his country on January 14, 2011, and to the resignation of Hosni Mubarak on February 11, 2011. Besides the great deal of media attention received by these events, the Tunisian and Egyptian revolutions also triggered an intense flurry of editing activity and heated discussions on the online encyclopedia Wikipedia. -
An End-To-End Learning Solution for Assessing the Quality of Wikipedia Articles Quang-Vinh Dang, Claudia-Lavinia Ignat
An end-to-end learning solution for assessing the quality of Wikipedia articles Quang-Vinh Dang, Claudia-Lavinia Ignat To cite this version: Quang-Vinh Dang, Claudia-Lavinia Ignat. An end-to-end learning solution for assessing the quality of Wikipedia articles. OpenSym 2017 - International Symposium on Open Collaboration, Aug 2017, Galway, Ireland. 10.1145/3125433.3125448. hal-01559693v3 HAL Id: hal-01559693 https://hal.inria.fr/hal-01559693v3 Submitted on 28 Jul 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. An end-to-end learning solution for assessing the quality of Wikipedia articles Quang-Vinh Dang Claudia-Lavinia Ignat Université de Lorraine, LORIA, F-54506 Inria, F-54600 Inria, F-54600 Université de Lorraine, LORIA, F-54506 CNRS, LORIA, F-54506 CNRS, LORIA, F-54506 [email protected] [email protected] ABSTRACT contains about 42 million articles in all languages with 5:4 Wikipedia is considered as the largest knowledge repository million articles belonging to English Wikipedia, as the result in the history of humanity and plays a crucial role in modern of the contribution from around 29 million users1. -
Digital Inclusion the Vital Role of Local Content
Special Issue A quarterly journal published by MIT Press innovations TECHNOLOGY | GOVERNANCE | GLOBALIZATION Digital Inclusion The Vital Role of Local Content Lead Essays Christopher Burns and Jonathan Dolan Building a Foundation for Digital Inclusion Mark Graham Inequitable Distributions in Internet Geographies Matthew Guilford To the Next Billion Case Narratives Sara Chamberlain A Mobile Guide Toward Better Health Kerry Harwin and Rikin Gandhi A Social Network for Farmer Training Analysis and Perspectives on Policy Mark Surman, Corina Gardner & David Ascher Local Content & Smartphones Emrys Schoemaker The Mobile Web Lesley-Anne Long, Sara Chamberlain & Kirsten Gagnaire The 80-20 Debate Marco Veremis Hyper-Local Content Is Key—Especially Social Media Abigail Steinberg, Peres Were & Amolo Ng’weno Democratizing Legal Information Across Africa Ravi Chhatpar and Robert Fabricant Digital Design for Emerging Markets Iris Orriss The Internet’s Language Barrier Kul Wadhwa & Howie Fung Converting Western Internet to Indigenous Internet ENTREPRENEURIAL SOLUTIONS TO GLOBAL CHALLENGES Editors Advisory Board Philip Auerswald Susan Davis Iqbal Quadir Bill Drayton David Kellogg Managing Editor Eric Lemelson Michael Youngblood Granger Morgan Guest Editors Jacqueline Novogratz Audrey Hyland James Turner Nicholas Sullivan Xue Lan Senior Associate Editor Editorial Board Robin Miller David Audretsch Matthew Bunn Associate Editors Maryann Feldman Dody Riggs Richard Florida Helen Snively Peter Mandaville Strategic Advisor Julia Novy-Hildesley Erin Krampetz Francisco Veloso Yang Xuedong Innovations: Technology | Governance | Globalization is co-hosted by the School of Public Policy, George Mason University (Fairfax, VA, USA); the Belfer Center for Science and International Affairs, Kennedy School of Government, Harvard University (Cambridge, MA, USA); and the Legatum Center for Development and Entrepreneurship, Massachusetts Institute of Technology (Cambridge, MA, USA). -
Using Topical Networks to Detect Editor Communities in Wikipedias
Using Topical Networks to Detect Editor Communities in Wikipedias Michael Kretschmer Bernhard Goschlberger¨ Ralf Klamma Advanced Community Research Studio Data Science Advanced Community Information Systems (ACIS), Research Studios Austria FG Information Systems (ACIS), Chair of Computer Science 5 Leopoldskronstr. 30, 5020 Salzburg, Austria Chair of Computer Science 5 (Information Systems & Databases), [email protected] (Information Systems & Databases), RWTH Aachen University RWTH Aachen University Ahornstr. 55, 52074 Aachen, Germany Ahornstr. 55, 52074 Aachen, Germany [email protected] [email protected] Abstract—The collaboration of Wikipedia editors is well re- a helpful tool in supporting editors to find articles to improve searched, covered by scientific works of many different fields. [6]. In recent years different designs of recommender systems There is a growing interest to implement recommender systems have been proposed [7], [8] to personalize these suggestions. that guide inexperienced editors to projects which fit their interests in certain topical domains. Although there have been Morgan and Halfaker identified the sense of community a new numerous studies focusing on editing behavior in Wikipedia the Wikipedia editors experiences as an important factor related to role of topical domains in this regard is still unclear. In particular, the retention rate in a recent report [9]. These subcommunities topical aspects of co-authorship are generally neglected. In this within Wikipedia are the driving force behind article creation paper, we want to determine by which criteria editors usually and elaboration [10]. We are therefore interested in analyzing choose articles they want to contribute to. We analyzed three different language editions of Wikipedia (Vietnamese, Hebrew, these editor communities and investigate how topical domains and Serbo-Croatian) by building social networks and running relate to communities of Wikipedia contributors across differ- community detection algorithms on them, i.e. -
Wikimedia Research Newsletter Volume 4 (2014) Contents
Wikimedia Research Newsletter Volume 4 (2014) Contents 1 About 1 1.1 Facts and figures ............................................ 1 1.2 How to subscribe ........................................... 1 1.3 How to contribute ........................................... 2 1.4 Open access vs. closed access publications .............................. 2 1.5 Archives ................................................ 3 1.5.1 Volume 6 (2016) ....................................... 3 1.5.2 Volume 5 (2015) ....................................... 3 1.5.3 Volume 4 (2014) ....................................... 3 1.5.4 Volume 3 (2013) ....................................... 3 1.5.5 Volume 2 (2012) ....................................... 3 1.5.6 Volume 1 (2011) ....................................... 4 1.5.7 Search the WRN archives ................................... 4 1.6 Contact ................................................ 4 2 Issue 4(1): January 2014 5 2.0.1 Translation students embrace Wikipedia assignments, but find user interface frustrating ... 5 2.1 Briefly ................................................. 6 2.1.1 References .......................................... 7 3 Issue 4(2): February 2014 8 3.0.2 CSCW '14 retrospective ................................... 8 3.0.3 Clustering Wikipedia editors by their biases ......................... 9 3.0.4 Monthly research showcase launched ............................. 9 3.0.5 Study of AfD debates: Did the SOPA protests mellow deletionists? ............. 9 3.0.6 Word frequency analysis identifies “four -
Lexbank: a Multilingual Lexical Resource for Low-Resource
LEXBANK: A MULTILINGUAL LEXICAL RESOURCE FOR LOW-RESOURCE LANGUAGES by Feras Ali Al Tarouti M.S., King Fahd University of Petroleum & Minerals, 2008 B.S., University of Dammam, 2001 A dissertation submitted to the Graduate Faculty of the University of Colorado Colorado Springs in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Computer Science 2016 ii © Copyright by Feras Ali Al Tarouti 2016 All Rights Reserved iii This dissertation for Doctor of Philosophy degree by Feras Ali Al Tarouti has been approved for the Department of Computer Science by Jugal Kalita, Chair Tim Chamillard Rory Lewis Khang Nhut Lam Sudhanshu Semwal Date iv Al Tarouti, Feras A. (Ph.D., Computer Science) LexBank: A Multilingual Lexical Resource for Low-Resource Languages Dissertation directed by Professor Jugal Kalita In this dissertation, we present new methods to create essential lexical resources for low-resource languages. Specifically, we develop methods for enhancing automatically cre- ated wordnets. As a baseline, we start by producing core wordnets, for several languages, using methods that need limited freely available resources for creating lexical resources (Lam et al., 2014a,b, 2015b). Then, we establish the semantic relations between synsets in wordnets we create. Next, we introduce a new method to automatically add glosses to the synsets in our wordnets. Our techniques use limited resources as input to ensure that they can be felicitously used with languages that currently lack many original resources. Most existing research works with languages that have significant lexical resources available, which are costly to construct. To make our created lexical resources publicly available, we developed LexBank which is a web-based system that provides language services for several low-resource languages. -
Comscore Trend Data on WMF Sites, As of Mar 09
Geography : Worldwide Location : All Locations Target : Total Audience Media : Wikimedia Foundation Sites Measures : Total Unique Visitors (000) 9/07 10/07 11/07 12/07 1/08 2/08 3/08 4/08 5/08 6/08 7/08 8/08 9/08 10/08 11/08 12/08 1/09 2/09 3/09 Total Internet : Total Audience 797,836 804,546 810,779 815,797 824,435 822,990 840,590 849,580 853,119 860,514 949,583 960,198 971,945 984,396 996,304 1,007,730 1,020,582 1,078,911 1,092,598 [P] Wikimedia Foundation Sites 228,830 244,474 241,533 226,119 242,554 240,754 256,061 261,414 263,120 251,502 244,326 248,539 272,109 277,208 280,969 272,998 289,811 300,751 327,148 [M] WIKIPEDIA.ORG 227,754 243,312 240,169 224,762 241,165 239,468 254,645 259,885 261,526 250,003 242,302 246,587 269,697 275,117 279,011 270,297 287,562 298,530 324,702 [C] English Wikipedia 132,961 140,710 143,373 143,470 141,929 153,661 156,015 166,188 [C] Spanish Wikipedia 22,558 25,388 26,412 25,411 21,912 22,513 26,151 30,544 [C] Japanese Wikipedia 25,946 25,698 25,961 25,591 25,103 27,997 26,299 27,981 [C] French Wikipedia 13,095 16,428 18,494 19,195 18,057 19,404 21,542 23,685 [C] German Wikipedia 18,506 20,435 20,474 21,238 20,940 22,237 21,802 23,191 [C] Portugese Wikipedia 9,948 10,788 9,606 10,014 7,980 7,853 9,343 12,218 [C] Italian Wikipedia 6,732 8,638 8,862 9,000 9,231 9,669 9,749 10,549 [C] Russian Wikipedia 5,119 6,535 7,101 7,699 8,761 9,222 8,275 9,459 [C] Arabic Wikipedia 1,539 1,938 2,429 2,689 2,111 2,424 6,839 8,363 [C] Vietnamese Wikipedia 1,625 2,434 2,451 2,857 3,138 3,359 4,454 4,942 [C] Chinese Wikipedias -
A Knowledge Base from Multilingual Wikipedias – YAGO3
A Knowledge Base from Multilingual Wikipedias { YAGO3 Une base de connaissances des Wikip´ediasplurilingues { YAGO3 Farzaneh Mahdisoltani Max Planck Institute for Informatics, Germany Joanna Biega Max Planck Institute for Informatics, Germany Fabian M. Suchanek T´el´ecomParisTech, France August 2014 Abstract We present YAGO3, an extension of the YAGO knowledge base that combines the information from the Wikipedias in multiple languages. Our technique fuses the multilingual information with the English WordNet to build one coherent knowledge base. We make use of the categories, the infoboxes, and Wikidata, and discover the meaning of infobox attributes across languages. We run our method on 10 different languages, and achieve a precision of 95%-100% in the attribute mapping. Our technique enlarges YAGO by 1m new entities and 7m new facts. R´esum´e Nous pr´esentons YAGO3, une extension de la base de connaissances YAGO, qui combine les informations provenant de Wikip´ediasen plusieurs langues. Notre technique combine l'information plurilingue avec la version anglaise de WordNet afin de cr´eer une base de connaissance coh´erente. Nous utilisons les cat´egories,les infoboxes, et Wikidata, et nous d´ecouvronsainsi la signification des attributs des infoboxes pour chaque langue. Nous utilisons notre m´ethode sur 10 langues, et nous obtenons une pr´ecisionde 95%-100% pour la correspondance des attributs entre eux. Notre technique ´etoffeYAGO avec 1m de nouvelles entit´eset 7 millions de nouveaux faits. 1 1 Introduction Motivation. Wikipedia1 is one of the most popular online encyclopedias. Sev- eral projects construct knowledge bases (KBs) from Wikipedia, with some of the most prominent projects being DBpedia [3], Freebase2, and YAGO [23]. -
Converting Western Internet to Indigenous Internet Lessons from Wikipedia
Kul Wadhwa and Howie Fung Converting Western Internet to Indigenous Internet Lessons from Wikipedia With the massive proliferation of communications technology, it’s the first time in human history where the majority of people (more than 4 billion) have access to information through a mobile phone. But then we have to ask: What content? Who contributes? In which languages? How should it be presented? And in what ways should it be delivered? And, most importantly, what are all the pieces you need to put together to make this work? The only Internet project that has been able to scale globally is Wikipedia. Everyone involved with this project got behind the vision of “a world in which every single human being can freely share in the sum of all knowledge.” Starting in 2001, this community was initially limited to people that had desktop or laptop computers, access to the Internet, and a strong comprehension of one of the 10 or so major languages on the planet. Wikipedia has consistently ranked in the top 10 most visited websites on the planet,1 as a knowledge resource that is multilingual and available in over 280 languages.2 Not only is it open and free to use, anyone with Internet access can write and make changes to Wikipedia articles. Therefore, as a democratic platform for both contribution and dissemination of information, it makes sense just to leverage it for greater use in the developing world, where access to such resources are either underdeveloped or are largely unavailable. But what made Wikipedia successful can’t be exported “as is” to the develop- ing world. -
Modeling Popularity and Reliability of Sources in Multilingual Wikipedia
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 31 March 2020 doi:10.20944/preprints202003.0460.v1 Peer-reviewed version available at Information 2020, 11; doi:10.3390/info11050263 Article Modeling Popularity and Reliability of Sources in Multilingual Wikipedia Włodzimierz Lewoniewski 1 , Krzysztof W˛ecel 1 and Witold Abramowicz 1 1 Department of Information Systems, Pozna´nUniversity of Economics and Business, Poland; {wlodzimierz.lewoniewski,krzysztof.wecel,witold.abramowicz}@ue.poznan.pl Abstract: One of the most important factors impacting quality of content in Wikipedia is presence of credible sources. By following references readers can verify facts or find more details about described topic. A Wikipedia article can be edited independently in any of over 300 languages, even by anonymous users, therefore information about the same topic may be inconsistent. This also applies to use of references in different language versions of a particular article, so the same statement can have different sources. In this paper we analyzed over 40 million articles from the 55 most developed language versions of Wikipedia to extract information about nearly 200 million references and find the most popular and reliable sources. We presented 10 models for the assessment of the popularity and reliability of the sources based on analysis of meta information about the references in Wikipedia articles, page views and authors of the articles. Using DBpedia and Wikidata we automatically identified the alignment of the sources to a specific domain. Additionally, we analyzed the changes of popularity and reliability in time and identified growth leaders in each considered months. The results can be used for quality improvements of the content in different languages versions of Wikipedia. -
Analyzing Accessibility of Wikipedia Projects Around the World
Analyzing Accessibility of Wikipedia Projects Around the World The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Clark, Justin, Robert Faris, Rebekah Heacock Jones. 2017. Analyzing Accessibility of Wikipedia Projects Around the World. Berkman Klein Center for Internet & Society Research Publication. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:32741922 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Analyzing Accessibility of Wikipedia Projects Around the World May 2017 Analyzing Accessibility of Wikipedia Projects Around the World Justin Clark Robert Faris Rebekah Heacock Jones INTERNET MONITOR is a research project to evaluate, describe, and summarize the means, mechanisms, and extent of Internet content controls and Internet activity around the world. thenetmonitor.org INTERNET MONITOR is a project of the Berkman Center for Internet & Society. http://cyber.harvard.edu 23 Everett Street • Second Floor • Cambridge, Massachusetts 02138 +1 617.495.7547 • +1 617.495.7641 (fax) • http://cyber.harvard.edu • [email protected] ABSTRACT This study, conducted by the Internet Monitor project at the Berkman Klein Center for Internet & Society, analyzes the scope of government-sponsored censorship of Wikimedia sites around the world. The study finds that, as of June 2016, China was likely censoring the Chinese language Wikipedia project, and Thailand and Uzbekistan were likely interfering intermittently with specific language projects of Wikipedia as well.