Explaining Cultural Borders on Wikipedia Through Multilingual Co-Editing Activity
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Cultural Anthropology Through the Lens of Wikipedia: Historical Leader Networks, Gender Bias, and News-Based Sentiment
Cultural Anthropology through the Lens of Wikipedia: Historical Leader Networks, Gender Bias, and News-based Sentiment Peter A. Gloor, Joao Marcos, Patrick M. de Boer, Hauke Fuehres, Wei Lo, Keiichi Nemoto [email protected] MIT Center for Collective Intelligence Abstract In this paper we study the differences in historical World View between Western and Eastern cultures, represented through the English, the Chinese, Japanese, and German Wikipedia. In particular, we analyze the historical networks of the World’s leaders since the beginning of written history, comparing them in the different Wikipedias and assessing cultural chauvinism. We also identify the most influential female leaders of all times in the English, German, Spanish, and Portuguese Wikipedia. As an additional lens into the soul of a culture we compare top terms, sentiment, emotionality, and complexity of the English, Portuguese, Spanish, and German Wikinews. 1 Introduction Over the last ten years the Web has become a mirror of the real world (Gloor et al. 2009). More recently, the Web has also begun to influence the real world: Societal events such as the Arab spring and the Chilean student unrest have drawn a large part of their impetus from the Internet and online social networks. In the meantime, Wikipedia has become one of the top ten Web sites1, occasionally beating daily newspapers in the actuality of most recent news. Be it the resignation of German national soccer team captain Philipp Lahm, or the downing of Malaysian Airlines flight 17 in the Ukraine by a guided missile, the corresponding Wikipedia page is updated as soon as the actual event happened (Becker 2012. -
Universality, Similarity, and Translation in the Wikipedia Inter-Language Link Network
In Search of the Ur-Wikipedia: Universality, Similarity, and Translation in the Wikipedia Inter-language Link Network Morten Warncke-Wang1, Anuradha Uduwage1, Zhenhua Dong2, John Riedl1 1GroupLens Research Dept. of Computer Science and Engineering 2Dept. of Information Technical Science University of Minnesota Nankai University Minneapolis, Minnesota Tianjin, China {morten,uduwage,riedl}@cs.umn.edu [email protected] ABSTRACT 1. INTRODUCTION Wikipedia has become one of the primary encyclopaedic in- The world: seven seas separating seven continents, seven formation repositories on the World Wide Web. It started billion people in 193 nations. The world's knowledge: 283 in 2001 with a single edition in the English language and has Wikipedias totalling more than 20 million articles. Some since expanded to more than 20 million articles in 283 lan- of the content that is contained within these Wikipedias is guages. Criss-crossing between the Wikipedias is an inter- probably shared between them; for instance it is likely that language link network, connecting the articles of one edition they will all have an article about Wikipedia itself. This of Wikipedia to another. We describe characteristics of ar- leads us to ask whether there exists some ur-Wikipedia, a ticles covered by nearly all Wikipedias and those covered by set of universal knowledge that any human encyclopaedia only a single language edition, we use the network to under- will contain, regardless of language, culture, etc? With such stand how we can judge the similarity between Wikipedias a large number of Wikipedia editions, what can we learn based on concept coverage, and we investigate the flow of about the knowledge in the ur-Wikipedia? translation between a selection of the larger Wikipedias. -
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. -
Collaboration: Interoperability Between People in the Creation of Language Resources for Less-Resourced Languages a SALTMIL Workshop May 27, 2008 Workshop Programme
Collaboration: interoperability between people in the creation of language resources for less-resourced languages A SALTMIL workshop May 27, 2008 Workshop Programme 14:30-14:35 Welcome 14:35-15:05 Icelandic Language Technology Ten Years Later Eiríkur Rögnvaldsson 15:05-15:35 Human Language Technology Resources for Less Commonly Taught Languages: Lessons Learned Toward Creation of Basic Language Resources Heather Simpson, Christopher Cieri, Kazuaki Maeda, Kathryn Baker, and Boyan Onyshkevych 15:35-16:05 Building resources for African languages Karel Pala, Sonja Bosch, and Christiane Fellbaum 16:05-16:45 COFFEE BREAK 16:45-17:15 Extracting bilingual word pairs from Wikipedia Francis M. Tyers and Jacques A. Pienaar 17:15-17:45 Building a Basque/Spanish bilingual database for speaker verification Iker Luengo, Eva Navas, Iñaki Sainz, Ibon Saratxaga, Jon Sanchez, Igor Odriozola, Juan J. Igarza and Inma Hernaez 17:45-18:15 Language resources for Uralic minority languages Attila Novák 18:15-18:45 Eslema. Towards a Corpus for Asturian Xulio Viejo, Roser Saurí and Angel Neira 18:45-19:00 Annual General Meeting of the SALTMIL SIG i Workshop Organisers Briony Williams Language Technologies Unit Bangor University, Wales, UK Mikel L. Forcada Departament de Llenguatges i Sistemes Informàtics Universitat d'Alacant, Spain Kepa Sarasola Lengoaia eta Sistema Informatikoak Saila Euskal Herriko Unibertsitatea / University of the Basque Country SALTMIL Speech and Language Technologies for Minority Languages A SIG of the International Speech Communication Association -
The Culture of Wikipedia
Good Faith Collaboration: The Culture of Wikipedia Good Faith Collaboration The Culture of Wikipedia Joseph Michael Reagle Jr. Foreword by Lawrence Lessig The MIT Press, Cambridge, MA. Web edition, Copyright © 2011 by Joseph Michael Reagle Jr. CC-NC-SA 3.0 Purchase at Amazon.com | Barnes and Noble | IndieBound | MIT Press Wikipedia's style of collaborative production has been lauded, lambasted, and satirized. Despite unease over its implications for the character (and quality) of knowledge, Wikipedia has brought us closer than ever to a realization of the centuries-old Author Bio & Research Blog pursuit of a universal encyclopedia. Good Faith Collaboration: The Culture of Wikipedia is a rich ethnographic portrayal of Wikipedia's historical roots, collaborative culture, and much debated legacy. Foreword Preface to the Web Edition Praise for Good Faith Collaboration Preface Extended Table of Contents "Reagle offers a compelling case that Wikipedia's most fascinating and unprecedented aspect isn't the encyclopedia itself — rather, it's the collaborative culture that underpins it: brawling, self-reflexive, funny, serious, and full-tilt committed to the 1. Nazis and Norms project, even if it means setting aside personal differences. Reagle's position as a scholar and a member of the community 2. The Pursuit of the Universal makes him uniquely situated to describe this culture." —Cory Doctorow , Boing Boing Encyclopedia "Reagle provides ample data regarding the everyday practices and cultural norms of the community which collaborates to 3. Good Faith Collaboration produce Wikipedia. His rich research and nuanced appreciation of the complexities of cultural digital media research are 4. The Puzzle of Openness well presented. -
Arxiv:2010.11856V3 [Cs.CL] 13 Apr 2021 Questions from Non-English Native Speakers to Rep- Information-Seeking Questions—Questions from Resent Real-World Applications
XOR QA: Cross-lingual Open-Retrieval Question Answering Akari Asaiº, Jungo Kasaiº, Jonathan H. Clark¶, Kenton Lee¶, Eunsol Choi¸, Hannaneh Hajishirziº¹ ºUniversity of Washington ¶Google Research ¸The University of Texas at Austin ¹Allen Institute for AI {akari, jkasai, hannaneh}@cs.washington.edu {jhclark, kentonl}@google.com, [email protected] Abstract ロン・ポールの学部時代の専攻は?[Japanese] (What did Ron Paul major in during undergraduate?) Multilingual question answering tasks typi- cally assume that answers exist in the same Multilingual document collections language as the question. Yet in prac- (Wikipedias) tice, many languages face both information ロン・ポール (ja.wikipedia) scarcity—where languages have few reference 高校卒業後はゲティスバーグ大学へ進学。 (After high school, he went to Gettysburg College.) articles—and information asymmetry—where questions reference concepts from other cul- Ron Paul (en.wikipedia) tures. This work extends open-retrieval ques- Paul went to Gettysburg College, where he was a member of the Lambda Chi Alpha fraternity. He tion answering to a cross-lingual setting en- graduated with a B.S. degree in Biology in 1957. abling questions from one language to be an- swered via answer content from another lan- 生物学 (Biology) guage. We construct a large-scale dataset built on 40K information-seeking questions Figure 1: Overview of XOR QA. Given a question in across 7 diverse non-English languages that Li, the model finds an answer in either English or Li TYDI QA could not find same-language an- Wikipedia and returns an answer in English or L . L swers for. Based on this dataset, we introduce i i is one of the 7 typologically diverse languages. -
The Case of Croatian Wikipedia: Encyclopaedia of Knowledge Or Encyclopaedia for the Nation?
The Case of Croatian Wikipedia: Encyclopaedia of Knowledge or Encyclopaedia for the Nation? 1 Authorial statement: This report represents the evaluation of the Croatian disinformation case by an external expert on the subject matter, who after conducting a thorough analysis of the Croatian community setting, provides three recommendations to address the ongoing challenges. The views and opinions expressed in this report are those of the author and do not necessarily reflect the official policy or position of the Wikimedia Foundation. The Wikimedia Foundation is publishing the report for transparency. Executive Summary Croatian Wikipedia (Hr.WP) has been struggling with content and conduct-related challenges, causing repeated concerns in the global volunteer community for more than a decade. With support of the Wikimedia Foundation Board of Trustees, the Foundation retained an external expert to evaluate the challenges faced by the project. The evaluation, conducted between February and May 2021, sought to assess whether there have been organized attempts to introduce disinformation into Croatian Wikipedia and whether the project has been captured by ideologically driven users who are structurally misaligned with Wikipedia’s five pillars guiding the traditional editorial project setup of the Wikipedia projects. Croatian Wikipedia represents the Croatian standard variant of the Serbo-Croatian language. Unlike other pluricentric Wikipedia language projects, such as English, French, German, and Spanish, Serbo-Croatian Wikipedia’s community was split up into Croatian, Bosnian, Serbian, and the original Serbo-Croatian wikis starting in 2003. The report concludes that this structure enabled local language communities to sort by points of view on each project, often falling along political party lines in the respective regions. -
Measuring Wikipedia PREPRINT 2005-04-12
Jakob Voss: Measuring Wikipedia PREPRINT 2005-04-12 * Measuring Wikipedia Jakob Voß (Humboldt-University of Berlin, Institute for library science) [email protected] Abstract: Wikipedia, an international project that uses Wiki software to collaboratively create an encyclopaedia, is becoming more and more popular. Everyone can directly edit articles and every edit is recorded. The version history of all articles is freely available and allows a multitude of examinations. This paper gives an overview on Wikipedia research. Wikipedia’s fundamental components, i.e. articles, authors, edits, and links, as well as con- tent and quality are analysed. Possibilities of research are explored including examples and first results. Several characteristics that are found in Wikipedia, such as exponential growth and scale-free networks are already known in other context. However the Wiki architecture also possesses some intrinsic specialities. General trends are measured that are typical for all Wikipedias but vary between languages in detail. Introduction Wikipedia is an international online project which attempts to create a free encyclopaedia in multiple languages. Using Wiki software, thousand of volunteers have collaboratively and successfully edited articles. Within three years, the world’s largest Open Content project has achieved more than 1.500.000 articles, outnumbering all other encyclopaedias. Still there is little research about the pro- ject or on Wikis at all.1 Most reflection on Wikipedia is raised within the community of its contribut- ors. This paper gives a first overview and outlook on Wikipedia research. Wikipedia is particularly in- teresting to cybermetric research because of the richness of phenomena and because its data is fully accessible. -
12€€€€Collaborating on the Sum of All Knowledge Across Languages
Wikipedia @ 20 • ::Wikipedia @ 20 12 Collaborating on the Sum of All Knowledge Across Languages Denny Vrandečić Published on: Oct 15, 2020 Updated on: Nov 16, 2020 License: Creative Commons Attribution 4.0 International License (CC-BY 4.0) Wikipedia @ 20 • ::Wikipedia @ 20 12 Collaborating on the Sum of All Knowledge Across Languages Wikipedia is available in almost three hundred languages, each with independently developed content and perspectives. By extending lessons learned from Wikipedia and Wikidata toward prose and structured content, more knowledge could be shared across languages and allow each edition to focus on their unique contributions and improve their comprehensiveness and currency. Every language edition of Wikipedia is written independently of every other language edition. A contributor may consult an existing article in another language edition when writing a new article, or they might even use the content translation tool to help with translating one article to another language, but there is nothing to ensure that articles in different language editions are aligned or kept consistent with each other. This is often regarded as a contribution to knowledge diversity since it allows every language edition to grow independently of all other language editions. So would creating a system that aligns the contents more closely with each other sacrifice that diversity? Differences Between Wikipedia Language Editions Wikipedia is often described as a wonder of the modern age. There are more than fifty million articles in almost three hundred languages. The goal of allowing everyone to share in the sum of all knowledge is achieved, right? Not yet. The knowledge in Wikipedia is unevenly distributed.1 Let’s take a look at where the first twenty years of editing Wikipedia have taken us. -
Classification of Wikipedia Articles Using BERT in Combination with Metadata
Daniel Garber¨ Classification of Wikipedia Articles using BERT in Combination with Metadata Bachelor’s Thesis to achieve the university degree of Bachelor of Science Bachelor’s degree programme: Soware Engineering and Management submied to Graz University of Technology Supervisor Dipl.-Ing. Dr.techn. Roman Kern Institute for Interactive Systems and Data Science Head: Univ.-Prof. Dipl.-Inf. Dr. Stefanie Lindstaedt Graz, August 2020 Affidavit I declare that I have authored this thesis independently, that I have not used other than the declared sources/resources, and that I have explicitly indicated all material which has been quoted either literally or by content from the sources used. The text document uploaded to tucnazonline is identical to the present master's thesis. Signature Abstract Wikipedia is the biggest online encyclopedia and it is continually growing. As its complexity increases, the task of assigning the appropriate categories to articles becomes more dicult for authors. In this work we used machine learning to auto- matically classify Wikipedia articles from specic categories. e classication was done using a variation of text and metadata features, including the revision history of the articles. e backbone of our classication model was a BERT model that was modied to be combined with metadata. We conducted two binary classication experiments and in each experiment compared various feature combinations. In the rst experiment we used articles from the category ”Emerging technologies” and ”Biotechnology”, where the best feature combination achieved an F1 score of 91.02%. For the second experiment the ”Biotechnology” articles are exchanged with random Wikipedia articles. Here the best feature combination achieved an F1 score of 97.81%. -
The Case of 13 Wikipedia Instances
Interaction Design and Architecture(s) Journal - IxD&A, N.22, 2014, pp. 34-47 The Impact of Culture On Smart Community Technology: The Case of 13 Wikipedia Instances Zinayida Petrushyna1, Ralf Klamma1, Matthias Jarke1,2 1 Advanced Community Information Systems Group, Information Systems and Databases Chair, RWTH Aachen University, Ahornstrasse 55, 52056 Aachen, Germany 2 Fraunhofer Institute for Applied Information Technology FIT, 53754 St. Augustin, Germany {petrushyna, klamma}@dbis.rwth-aachen.de [email protected] Abstract Smart communities provide technologies for monitoring social behaviors inside communities. The technologies that support knowledge building should consider the cultural background of community members. The studies of the influence of the culture on knowledge building is limited. Just a few works consider digital traces of individuals that they explain using cultural values and beliefs. In this work, we analyze 13 Wikipedia instances where users with different cultural background build knowledge in different ways. We compare edits of users. Using social network analysis we build and analyze co- authorship networks and watch the networks evolution. We explain the differences we have found using Hofstede dimensions and Schwartz cultural values and discuss implications for the design of smart community technologies. Our findings provide insights in requirements for technologies used for smart communities in different cultures. Keywords: Social network analysis, Wikipedia communities, Hofstede dimensions, Schwartz cultural values 1 Introduction People prefer to leave in smart cities where their needs are satisfied [1]. The development of smart cities depends on the collaboration of individuals. The investigation of the flow [1] of knowledge created by the individuals allows the monitoring of city smartness. -
Dictionary of Slovenian Exonyms Explanatory Notes
GEOGRAFSKI INŠTITUT ANTONA MELIKA ZNANSTVENORAZISKOVALNI CENTER SLOVENSKE AKADEMIJE ZNANOSTI IN UMETNOSTI ANTON MELIK GEOGRAPHICAL INSTITUTE OF ZRC SAZU DICTIONARY OF SLOVENIAN EXONYMS EXPLANATORY NOTES Drago Kladnik Drago Perko AMGI ZRC SAZU Ljubljana 2013 1 Preface The geocoded collection of Slovenia exonyms Zbirka slovenskih eksonimov and the dictionary of Slovenina exonyms Slovar slovenskih eksonimov have been set up as part of the research project Slovenski eksonimi: metodologija, standardizacija, GIS (Slovenian Exonyms: Methodology, Standardization, GIS). They include more than 5,000 of the most frequently used exonyms that were collected from more than 50,000 documented various forms of these types of geographical names. The dictionary contains thirty-four categories and has been designed as a contribution to further standardization of Slovenian exonyms, which can be added to on an ongoing basis and used to find information on Slovenian exonym usage. Currently, their use is not standardized, even though analysis of the collected material showed that the differences are gradually becoming smaller. The standardization of public, professional, and scholarly use will allow completely unambiguous identification of individual features and items named. By determining the etymology of the exonyms included, we have prepared the material for their final standardization, and by systematically documenting them we have ensured that this important aspect of the Slovenian language will not sink into oblivion. The results of this research will not only help preserve linguistic heritage as an important aspect of Slovenian cultural heritage, but also help preserve national identity. Slovenian exonyms also enrich the international treasury of such names and are undoubtedly important part of the world’s linguistic heritage.