Assessing Public Interest Based on Wikipedia's Most Visited Medical Articles During the SARS-Cov-2 Outbreak: Search Trends Analysis
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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. -
Amplifying the Impact of Open Access: Wikipedia and the Diffusion of Science
(forthcoming in the Journal of the Association for Information Science and Technology) Amplifying the Impact of Open Access: Wikipedia and the Diffusion of Science Misha Teplitskiy Grace Lu Eamon Duede Dept. of Sociology and KnowledgeLab Computation Institute and KnowledgeLab University of Chicago KnowledgeLab University of Chicago [email protected] University of Chicago [email protected] (773) 834-4787 [email protected] (773) 834-4787 5735 South Ellis Avenue (773) 834-4787 5735 South Ellis Avenue Chicago, Illinois 60637 5735 South Ellis Avenue Chicago, Illinois 60637 Chicago, Illinois 60637 Abstract With the rise of Wikipedia as a first-stop source for scientific knowledge, it is important to compare its representation of that knowledge to that of the academic literature. Here we identify the 250 most heavi- ly used journals in each of 26 research fields (4,721 journals, 19.4M articles in total) indexed by the Scopus database, and test whether topic, academic status, and accessibility make articles from these journals more or less likely to be referenced on Wikipedia. We find that a journal’s academic status (im- pact factor) and accessibility (open access policy) both strongly increase the probability of its being ref- erenced on Wikipedia. Controlling for field and impact factor, the odds that an open access journal is referenced on the English Wikipedia are 47% higher compared to paywall journals. One of the implica- tions of this study is that a major consequence of open access policies is to significantly amplify the dif- fusion of science, through an intermediary like Wikipedia, to a broad audience. Word count: 7894 Introduction Wikipedia, one of the most visited websites in the world1, has become a destination for information of all kinds, including information about science (Heilman & West, 2015; Laurent & Vickers, 2009; Okoli, Mehdi, Mesgari, Nielsen, & Lanamäki, 2014; Spoerri, 2007). -
Language-Agnostic Relation Extraction from Abstracts in Wikis
information Article Language-Agnostic Relation Extraction from Abstracts in Wikis Nicolas Heist, Sven Hertling and Heiko Paulheim * ID Data and Web Science Group, University of Mannheim, Mannheim 68131, Germany; [email protected] (N.H.); [email protected] (S.H.) * Correspondence: [email protected] Received: 5 February 2018; Accepted: 28 March 2018; Published: 29 March 2018 Abstract: Large-scale knowledge graphs, such as DBpedia, Wikidata, or YAGO, can be enhanced by relation extraction from text, using the data in the knowledge graph as training data, i.e., using distant supervision. While most existing approaches use language-specific methods (usually for English), we present a language-agnostic approach that exploits background knowledge from the graph instead of language-specific techniques and builds machine learning models only from language-independent features. We demonstrate the extraction of relations from Wikipedia abstracts, using the twelve largest language editions of Wikipedia. From those, we can extract 1.6 M new relations in DBpedia at a level of precision of 95%, using a RandomForest classifier trained only on language-independent features. We furthermore investigate the similarity of models for different languages and show an exemplary geographical breakdown of the information extracted. In a second series of experiments, we show how the approach can be transferred to DBkWik, a knowledge graph extracted from thousands of Wikis. We discuss the challenges and first results of extracting relations from a larger set of Wikis, using a less formalized knowledge graph. Keywords: relation extraction; knowledge graphs; Wikipedia; DBpedia; DBkWik; Wiki farms 1. Introduction Large-scale knowledge graphs, such as DBpedia [1], Freebase [2], Wikidata [3], or YAGO [4], are usually built using heuristic extraction methods, by exploiting crowd-sourcing processes, or both [5]. -
Defending Democracy & Kristin Skare Orgeret Nordicom-Information
Defending Defending Oslo 8–11 August 2013 Democracy The 2013 NordMedia conference in Oslo marked the 40 years that had passed since the very first Nordic media conference. To acknowledge this 40-year anniversary, it made sense to have a conference theme that dealt with a major and important topic: Defending Democracy. Nordic Defending and Global Diversities in Media and Journalism. Focusing on the rela- tionship between journalism, other media practices and democracy, the plenary sessions raised questions such as: Democracy & Edited by What roles do media and journalism play in democratization • Kristin Skare Orgeret processes and what roles should they play? Nordic and Global Diversities How does the increasingly complex and omnipresent media in Media and Journalism • Hornmoen Harald field affect conditions for freedom of speech? This special issue contains the keynote speeches of Natalie Fenton, Stephen Ward and Ib Bondebjerg. A number of the conference papers have been revised and edited to become articles. Together, the articles presented should give the reader an idea of the breadth and depth of Edited by current Nordic scholarship in the area. Harald Hornmoen & Kristin Skare Orgeret SPECIAL ISSUE Nordicom Review | Volume 35 | August 2014 Nordicom-Information | Volume 36 | Number 2 | August 2014 Nordicom-Information Nordicom Review University of Gothenburg 2014 issue Special Box 713, SE 405 30 Göteborg, Sweden Telephone +46 31 786 00 00 (op.) | Fax +46 31 786 46 55 www.nordicom.gu.se | E-mail: [email protected] SPECIAL ISSUE Nordicom Review | Volume 35 | August 2014 Nordicom-Information | Volume 36 | Number 2 | August 2014 Nordicom Review Journal from the Nordic Information Centre for Media and Communication Research Editor NORDICOM invites media researchers to contri- Ulla Carlsson bute scientific articles, reviews, and debates. -
A Complete, Longitudinal and Multi-Language Dataset of the Wikipedia Link Networks
WikiLinkGraphs: A Complete, Longitudinal and Multi-Language Dataset of the Wikipedia Link Networks Cristian Consonni David Laniado Alberto Montresor DISI, University of Trento Eurecat, Centre Tecnologic` de Catalunya DISI, University of Trento [email protected] [email protected] [email protected] Abstract and result in a huge conceptual network. According to Wiki- pedia policies2 (Wikipedia contributors 2018e), when a con- Wikipedia articles contain multiple links connecting a sub- cept is relevant within an article, the article should include a ject to other pages of the encyclopedia. In Wikipedia par- link to the page corresponding to such concept (Borra et al. lance, these links are called internal links or wikilinks. We present a complete dataset of the network of internal Wiki- 2015). Therefore, the network between articles may be seen pedia links for the 9 largest language editions. The dataset as a giant mind map, emerging from the links established by contains yearly snapshots of the network and spans 17 years, the community. Such graph is not static but is continuously from the creation of Wikipedia in 2001 to March 1st, 2018. growing and evolving, reflecting the endless collaborative While previous work has mostly focused on the complete hy- process behind it. perlink graph which includes also links automatically gener- The English Wikipedia includes over 163 million con- ated by templates, we parsed each revision of each article to nections between its articles. This huge graph has been track links appearing in the main text. In this way we obtained exploited for many purposes, from natural language pro- a cleaner network, discarding more than half of the links and cessing (Yeh et al. -
Complete Issue
Culture Unbound: Journal of Current Cultural Research Thematic Section: Changing Orders of Knowledge? Encyclopedias in Transition Edited by Jutta Haider & Olof Sundin Extraction from Volume 6, 2014 Linköping University Electronic Press Culture Unbound: ISSN 2000-1525 (online) URL: http://www.cultureunbound.ep.liu.se/ © 2014 The Authors. Culture Unbound, Extraction from Volume 6, 2014 Thematic Section: Changing Orders of Knowledge? Encyclopedias in Transition Jutta Haider & Olof Sundin Introduction: Changing Orders of Knowledge? Encyclopaedias in Transition ................................ 475 Katharine Schopflin What do we Think an Encyclopaedia is? ........................................................................................... 483 Seth Rudy Knowledge and the Systematic Reader: The Past and Present of Encyclopedic Reading .............................................................................................................................................. 505 Siv Frøydis Berg & Tore Rem Knowledge for Sale: Norwegian Encyclopaedias in the Marketplace .............................................. 527 Vanessa Aliniaina Rasoamampianina Reviewing Encyclopaedia Authority .................................................................................................. 547 Ulrike Spree How readers Shape the Content of an Encyclopedia: A Case Study Comparing the German Meyers Konversationslexikon (1885-1890) with Wikipedia (2002-2013) ........................... 569 Kim Osman The Free Encyclopaedia that Anyone can Edit: The -
Wikimatrix: Mining 135M Parallel Sentences
Under review as a conference paper at ICLR 2020 WIKIMATRIX:MINING 135M PARALLEL SENTENCES IN 1620 LANGUAGE PAIRS FROM WIKIPEDIA Anonymous authors Paper under double-blind review ABSTRACT We present an approach based on multilingual sentence embeddings to automat- ically extract parallel sentences from the content of Wikipedia articles in 85 lan- guages, including several dialects or low-resource languages. We do not limit the extraction process to alignments with English, but systematically consider all pos- sible language pairs. In total, we are able to extract 135M parallel sentences for 1620 different language pairs, out of which only 34M are aligned with English. This corpus of parallel sentences is freely available.1 To get an indication on the quality of the extracted bitexts, we train neural MT baseline systems on the mined data only for 1886 languages pairs, and evaluate them on the TED corpus, achieving strong BLEU scores for many language pairs. The WikiMatrix bitexts seem to be particularly interesting to train MT systems between distant languages without the need to pivot through English. 1 INTRODUCTION Most of the current approaches in Natural Language Processing (NLP) are data-driven. The size of the resources used for training is often the primary concern, but the quality and a large variety of topics may be equally important. Monolingual texts are usually available in huge amounts for many topics and languages. However, multilingual resources, typically sentences in two languages which are mutual translations, are more limited, in particular when the two languages do not involve English. An important source of parallel texts are international organizations like the European Parliament (Koehn, 2005) or the United Nations (Ziemski et al., 2016). -
Using Natural Language Generation to Bootstrap Missing Wikipedia Articles
Semantic Web 0 (0) 1 1 IOS Press 1 1 2 2 3 3 4 Using Natural Language Generation to 4 5 5 6 Bootstrap Missing Wikipedia Articles: 6 7 7 8 8 9 A Human-centric Perspective 9 10 10 * 11 Lucie-Aimée Kaffee , Pavlos Vougiouklis and Elena Simperl 11 12 School of Electronics and Computer Science, University of Southampton, UK 12 13 E-mails: [email protected], [email protected], [email protected] 13 14 14 15 15 16 16 17 17 Abstract. Nowadays natural language generation (NLG) is used in everything from news reporting and chatbots to social media 18 18 management. Recent advances in machine learning have made it possible to train NLG systems that seek to achieve human- 19 19 level performance in text writing and summarisation. In this paper, we propose such a system in the context of Wikipedia and 20 evaluate it with Wikipedia readers and editors. Our solution builds upon the ArticlePlaceholder, a tool used in 14 under-resourced 20 21 Wikipedia language versions, which displays structured data from the Wikidata knowledge base on empty Wikipedia pages. 21 22 We train a neural network to generate a ’introductory sentence from the Wikidata triples shown by the ArticlePlaceholder, and 22 23 explore how Wikipedia users engage with it. The evaluation, which includes an automatic, a judgement-based, and a task-based 23 24 component, shows that the summary sentences score well in terms of perceived fluency and appropriateness for Wikipedia, and 24 25 can help editors bootstrap new articles. -
Wikipedia and Wikis Haider, Jutta
Wikipedia and Wikis Haider, Jutta; Sundin, Olof Published in: The Handbook of Peer Production DOI: 10.1002/9781119537151.ch13 2021 Document Version: Peer reviewed version (aka post-print) Link to publication Citation for published version (APA): Haider, J., & Sundin, O. (2021). Wikipedia and Wikis. In M. O'Neil, C. Pentzold, & S. Toupin (Eds.), The Handbook of Peer Production (pp. 169-184). (Wiley Handbooks in Communication and Media Series ). Wiley. https://doi.org/10.1002/9781119537151.ch13 Total number of authors: 2 Creative Commons License: CC BY-NC-ND General rights Unless other specific re-use rights are stated the following general rights apply: Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Read more about Creative commons licenses: https://creativecommons.org/licenses/ Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. LUND UNIVERSITY PO Box 117 221 00 Lund +46 46-222 00 00 This is the author’s version of a chapter accepted for publication in the Handbook of Peer Production. -
Wikipedia @ 20
Wikipedia @ 20 Wikipedia @ 20 Stories of an Incomplete Revolution Edited by Joseph Reagle and Jackie Koerner The MIT Press Cambridge, Massachusetts London, England © 2020 Massachusetts Institute of Technology This work is subject to a Creative Commons CC BY- NC 4.0 license. Subject to such license, all rights are reserved. The open access edition of this book was made possible by generous funding from Knowledge Unlatched, Northeastern University Communication Studies Department, and Wikimedia Foundation. This book was set in Stone Serif and Stone Sans by Westchester Publishing Ser vices. Library of Congress Cataloging-in-Publication Data Names: Reagle, Joseph, editor. | Koerner, Jackie, editor. Title: Wikipedia @ 20 : stories of an incomplete revolution / edited by Joseph M. Reagle and Jackie Koerner. Other titles: Wikipedia at 20 Description: Cambridge, Massachusetts : The MIT Press, [2020] | Includes bibliographical references and index. Identifiers: LCCN 2020000804 | ISBN 9780262538176 (paperback) Subjects: LCSH: Wikipedia--History. Classification: LCC AE100 .W54 2020 | DDC 030--dc23 LC record available at https://lccn.loc.gov/2020000804 Contents Preface ix Introduction: Connections 1 Joseph Reagle and Jackie Koerner I Hindsight 1 The Many (Reported) Deaths of Wikipedia 9 Joseph Reagle 2 From Anarchy to Wikiality, Glaring Bias to Good Cop: Press Coverage of Wikipedia’s First Two Decades 21 Omer Benjakob and Stephen Harrison 3 From Utopia to Practice and Back 43 Yochai Benkler 4 An Encyclopedia with Breaking News 55 Brian Keegan 5 Paid with Interest: COI Editing and Its Discontents 71 William Beutler II Connection 6 Wikipedia and Libraries 89 Phoebe Ayers 7 Three Links: Be Bold, Assume Good Faith, and There Are No Firm Rules 107 Rebecca Thorndike- Breeze, Cecelia A. -
The Handbook of Peer Production Chapter 13: Wikipedia and Wikis
This is the author’s version of a chapter accepted for publication in the Handbook of Peer Production. Changes resulting from the publishing process such as copy-editing, typesetting, and other quality control mechanisms may not be reflected in this document. This author manuscript version is available for personal, non-commercial and no derivative uses only. Citation: Haider, J. & Sundin, O. (2021). Wikipedia and wikis. In: M. O’Neil, C. Pentzold & S. Toupin (Eds.), The Handbook of Peer Production (pp. 169-184). Malden, MA: Wiley-Blackwell. ISBN 9781119537106 Available at: https://www.wiley.com/en-au/The+Handbook+of+Peer+Production-p-9781119537090 The Handbook of Peer Production Chapter 13: Wikipedia and Wikis Jutta Haider, University of Borås, Sweden & Olof Sundin, Lund University, Sweden Chapter 13 – Wikis and Wikipedia 2 1. Introduction WikiWikiWebs or wikis constitute the core platform of peer production. Wikis are software programs allowing for flexible collaboration without necessarily having a defined content owner or leader. A wiki is a user-editable website or content management system. Wikis might use different programming languages and licenses, but they apply the same model for cooperation, which means that collaborators can modify content, insert hyperlinks, and change the structure of a document directly in any web browser. Edits are usually archived and open to revision for all collaborators. The most popular and successful wiki-based project by far is Wikipedia. Established in 2001, today this encyclopedia is one of the most popular sites on the Web; what is more, with its data supporting other applications and commercial platforms like Google, Wikipedia has taken on an infrastructural role in the contemporary internet.