Information Access in a Multilingual World: Transitioning from Research to Real-World Applications
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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. -
International Journal of Computational Linguistics
International Journal of Computational Linguistics & Chinese Language Processing Aims and Scope International Journal of Computational Linguistics and Chinese Language Processing (IJCLCLP) is an international journal published by the Association for Computational Linguistics and Chinese Language Processing (ACLCLP). This journal was founded in August 1996 and is published four issues per year since 2005. This journal covers all aspects related to computational linguistics and speech/text processing of all natural languages. Possible topics for manuscript submitted to the journal include, but are not limited to: • Computational Linguistics • Natural Language Processing • Machine Translation • Language Generation • Language Learning • Speech Analysis/Synthesis • Speech Recognition/Understanding • Spoken Dialog Systems • Information Retrieval and Extraction • Web Information Extraction/Mining • Corpus Linguistics • Multilingual/Cross-lingual Language Processing Membership & Subscriptions If you are interested in joining ACLCLP, please see appendix for further information. Copyright © The Association for Computational Linguistics and Chinese Language Processing International Journal of Computational Linguistics and Chinese Language Processing is published four issues per volume by the Association for Computational Linguistics and Chinese Language Processing. Responsibility for the contents rests upon the authors and not upon ACLCLP, or its members. Copyright by the Association for Computational Linguistics and Chinese Language Processing. All rights reserved. No part of this journal may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical photocopying, recording or otherwise, without prior permission in writing form from the Editor-in Chief. Cover Calligraphy by Professor Ching-Chun Hsieh, founding president of ACLCLP Text excerpted and compiled from ancient Chinese classics, dating back to 700 B.C. -
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. -
China Date: 8 January 2007
Refugee Review Tribunal AUSTRALIA RRT RESEARCH RESPONSE Research Response Number: CHN31098 Country: China Date: 8 January 2007 Keywords: China – Taiwan Strait – 2006 Military exercises – Typhoons This response was prepared by the Country Research Section of the Refugee Review Tribunal (RRT) after researching publicly accessible information currently available to the RRT within time constraints. This response is not, and does not purport to be, conclusive as to the merit of any particular claim to refugee status or asylum. Questions 1. Is there corroborating information about military manoeuvres and exercises in Pingtan? 2. Is there any information specifically about the military exercise there in July 2006? 3. Is there any information about “Army day” on 1 August 2006? 4. What are the aquatic farming/fishing activities carried out in that area? 5. Has there been pollution following military exercises along the Taiwan Strait? 6. The delegate makes reference to independent information that indicates that from May until August 2006 China particularly the eastern coast was hit by a succession of storms and typhoons. The last one being the hardest to hit China in 50 years. Could I have information about this please? The delegate refers to typhoon Prapiroon. What information is available about that typhoon? 7. The delegate was of the view that military exercises would not be organised in typhoon season, particularly such a bad one. Is there any information to assist? RESPONSE 1. Is there corroborating information about military manoeuvres and exercises in Pingtan? 2. Is there any information specifically about the military exercise there in July 2006? There is a minor naval base in Pingtan and military manoeuvres are regularly held in the Taiwan Strait where Pingtan in located, especially in the June to August period. -
THE CASE of WIKIPEDIA Shane Greenstein Feng Zhu
NBER WORKING PAPER SERIES COLLECTIVE INTELLIGENCE AND NEUTRAL POINT OF VIEW: THE CASE OF WIKIPEDIA Shane Greenstein Feng Zhu Working Paper 18167 http://www.nber.org/papers/w18167 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 June 2012 The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer- reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications. © 2012 by Shane Greenstein and Feng Zhu. All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source. Collective Intelligence and Neutral Point of View: The Case of Wikipedia Shane Greenstein and Feng Zhu NBER Working Paper No. 18167 June 2012 JEL No. L17,L3,L86 ABSTRACT We examine whether collective intelligence helps achieve a neutral point of view using data from a decade of Wikipedia’s articles on US politics. Our null hypothesis builds on Linus’ Law, often expressed as “Given enough eyeballs, all bugs are shallow.” Our findings are consistent with a narrow interpretation of Linus’ Law, namely, a greater number of contributors to an article makes an article more neutral. No evidence supports a broad interpretation of Linus’ Law. Moreover, several empirical facts suggest the law does not shape many articles. The majority of articles receive little attention, and most articles change only mildly from their initial slant. -
A Natural Experiment at Chinese Wikipedia
American Economic Review 101 (June 2011): 1601–1615 http://www.aeaweb.org/articles.php?doi 10.1257/aer.101.4.1601 = Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia By Xiaoquan Michael Zhang and Feng Zhu* ( ) Many public goods on the Internet today rely entirely on free user contributions. Popular examples include open source software development communities e.g., ( Linux, Apache , open content production e.g., Wikipedia, OpenCourseWare , and ) ( ) content sharing networks e.g., Flickr, YouTube . Several studies have examined the ( ) incentives that motivate these free contributors e.g., Josh Lerner and Jean Tirole ( 2002; Karim R. Lakhani and Eric von Hippel 2003 . ) In this paper, we examine the causal relationship between group size and incen- tives to contribute in the setting of Chinese Wikipedia, the Chinese language ver- sion of an online encyclopedia that relies entirely on voluntary contributions. The group at Chinese Wikipedia is composed of Chinese-speaking people in mainland China, Taiwan, Hong Kong, Singapore, and other regions in the world, who are aware of Chinese Wikipedia and have access to it. Our identification hinges on the exogenous reduction in group size at Chinese Wikipedia as a result of the block of Chinese Wikipedia in mainland China in October 2005. During the block, mainland Chinese could not use or contribute to Chinese Wikipedia, although contributors outside mainland China could continue to do so. We find that contribution levels of these nonblocked contributors decrease by 42.8 percent on average as a result of the block. We attribute the cause to social effects: contributors receive social benefits from their contributions, and the shrinking group size reduces these social benefits. -
100125-Wikimedia Feb Board Background Final2 Objectives for This Document
Wikimedia Foundation Board Meeting Pre-read January 2010 Imagine a world in which every single human being can freely share in the sum of all knowledge. That's our commitment. Contents • Strategic planning process update • Goal setting • Priority 1: Building the platform • Priority 2: Strengthening the editing community • Priority 3: Accelerating impact through innovation and experimentation • Implications for the Foundation TBG 100125-Wikimedia_Feb Board Background_Final2 Objectives for this document • Provide reminder on design of strategic planning process and current stage of work • Highlight research and analysis that informed the development of priorities for the Wikimedia Foundation • Introduce action items, including priorities for 2010-11 annual plan to be discussed at Board meeting in February TBG 100125-Wikimedia_Feb Board Background_Final3 A reminder: Two interdependent objectives for the planning work • Define a strategic direction that advances the Wikimedia vision over the next five years • Broader reach and participation • Improved quality and scope of content • Defined community roles and partnerships • Develop a business plan to guide Wikimedia Foundation in executing this direction • Organization, capabilities, and governance • Technology strategy and infrastructure • Economics, cost structure, and funding models TBG 100125-Wikimedia_Feb Board Background_Final4 Our frame for developing the strategic direction and Wikimedia Foundation’s business plan • Wikimedia’s vision is “a world in which every single human being can -
Explaining Cultural Borders on Wikipedia Through Multilingual Co-Editing Activity
Samoilenko et al. EPJ Data Science (2016)5:9 DOI 10.1140/epjds/s13688-016-0070-8 REGULAR ARTICLE OpenAccess Linguistic neighbourhoods: explaining cultural borders on Wikipedia through multilingual co-editing activity Anna Samoilenko1,2*, Fariba Karimi1,DanielEdler3, Jérôme Kunegis2 and Markus Strohmaier1,2 *Correspondence: [email protected] Abstract 1GESIS - Leibniz-Institute for the Social Sciences, 6-8 Unter In this paper, we study the network of global interconnections between language Sachsenhausen, Cologne, 50667, communities, based on shared co-editing interests of Wikipedia editors, and show Germany that although English is discussed as a potential lingua franca of the digital space, its 2University of Koblenz-Landau, Koblenz, Germany domination disappears in the network of co-editing similarities, and instead local Full list of author information is connections come to the forefront. Out of the hypotheses we explored, bilingualism, available at the end of the article linguistic similarity of languages, and shared religion provide the best explanations for the similarity of interests between cultural communities. Population attraction and geographical proximity are also significant, but much weaker factors bringing communities together. In addition, we present an approach that allows for extracting significant cultural borders from editing activity of Wikipedia users, and comparing a set of hypotheses about the social mechanisms generating these borders. Our study sheds light on how culture is reflected in the collective process -
Does Wikipedia Matter? the Effect of Wikipedia on Tourist Choices Marit Hinnosaar, Toomas Hinnosaar, Michael Kummer, and Olga Slivko Discus Si On Paper No
Dis cus si on Paper No. 15-089 Does Wikipedia Matter? The Effect of Wikipedia on Tourist Choices Marit Hinnosaar, Toomas Hinnosaar, Michael Kummer, and Olga Slivko Dis cus si on Paper No. 15-089 Does Wikipedia Matter? The Effect of Wikipedia on Tourist Choices Marit Hinnosaar, Toomas Hinnosaar, Michael Kummer, and Olga Slivko First version: December 2015 This version: September 2017 Download this ZEW Discussion Paper from our ftp server: http://ftp.zew.de/pub/zew-docs/dp/dp15089.pdf Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar. Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW. Does Wikipedia Matter? The Effect of Wikipedia on Tourist Choices ∗ Marit Hinnosaar† Toomas Hinnosaar‡ Michael Kummer§ Olga Slivko¶ First version: December 2015 This version: September 2017 September 25, 2017 Abstract We document a causal influence of online user-generated information on real- world economic outcomes. In particular, we conduct a randomized field experiment to test whether additional information on Wikipedia about cities affects tourists’ choices of overnight visits. -
Word Segmentation for Chinese Wikipedia Using N-Gram Mutual Information
Word Segmentation for Chinese Wikipedia Using N-Gram Mutual Information Ling-Xiang Tang1, Shlomo Geva1, Yue Xu1 and Andrew Trotman2 1School of Information Technology Faculty of Science and Technology Queensland University of Technology Queensland 4000 Australia {l4.tang, s.geva, yue.xu}@qut.edu.au 2Department of Computer Science Universityof Otago Dunedin 9054 New Zealand [email protected] Abstract In this paper, we propose an unsupervised seg- is called 激光打印机 in mainland China, but 鐳射打印機 in mentation approach, named "n-gram mutual information", or Hongkong, and 雷射印表機 in Taiwan. NGMI, which is used to segment Chinese documents into n- In digital representations of Chinese text different encoding character words or phrases, using language statistics drawn schemes have been adopted to represent the characters. How- from the Chinese Wikipedia corpus. The approach allevi- ever, most encoding schemes are incompatible with each other. ates the tremendous effort that is required in preparing and To avoid the conflict of different encoding standards and to maintaining the manually segmented Chinese text for train- cater for people's linguistic preferences, Unicode is often used ing purposes, and manually maintaining ever expanding lex- in collaborative work, for example in Wikipedia articles. With icons. Previously, mutual information was used to achieve Unicode, Chinese articles can be composed by people from all automated segmentation into 2-character words. The NGMI the above Chinese-speaking areas in a collaborative way with- approach extends the approach to handle longer n-character out encoding difficulties. As a result, these different forms of words. Experiments with heterogeneous documents from the Chinese writings and variants may coexist within same pages.