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A Topic-Aligned Multilingual Corpus of Wikipedia Articles for Studying Information Asymmetry in Low Resource Languages
Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 2373–2380 Marseille, 11–16 May 2020 c European Language Resources Association (ELRA), licensed under CC-BY-NC A Topic-Aligned Multilingual Corpus of Wikipedia Articles for Studying Information Asymmetry in Low Resource Languages Dwaipayan Roy, Sumit Bhatia, Prateek Jain GESIS - Cologne, IBM Research - Delhi, IIIT - Delhi [email protected], [email protected], [email protected] Abstract Wikipedia is the largest web-based open encyclopedia covering more than three hundred languages. However, different language editions of Wikipedia differ significantly in terms of their information coverage. We present a systematic comparison of information coverage in English Wikipedia (most exhaustive) and Wikipedias in eight other widely spoken languages (Arabic, German, Hindi, Korean, Portuguese, Russian, Spanish and Turkish). We analyze the content present in the respective Wikipedias in terms of the coverage of topics as well as the depth of coverage of topics included in these Wikipedias. Our analysis quantifies and provides useful insights about the information gap that exists between different language editions of Wikipedia and offers a roadmap for the Information Retrieval (IR) community to bridge this gap. Keywords: Wikipedia, Knowledge base, Information gap 1. Introduction other with respect to the coverage of topics as well as Wikipedia is the largest web-based encyclopedia covering the amount of information about overlapping topics. -
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. -
Omnipedia: Bridging the Wikipedia Language
Omnipedia: Bridging the Wikipedia Language Gap Patti Bao*†, Brent Hecht†, Samuel Carton†, Mahmood Quaderi†, Michael Horn†§, Darren Gergle*† *Communication Studies, †Electrical Engineering & Computer Science, §Learning Sciences Northwestern University {patti,brent,sam.carton,quaderi}@u.northwestern.edu, {michael-horn,dgergle}@northwestern.edu ABSTRACT language edition contains its own cultural viewpoints on a We present Omnipedia, a system that allows Wikipedia large number of topics [7, 14, 15, 27]. On the other hand, readers to gain insight from up to 25 language editions of the language barrier serves to silo knowledge [2, 4, 33], Wikipedia simultaneously. Omnipedia highlights the slowing the transfer of less culturally imbued information similarities and differences that exist among Wikipedia between language editions and preventing Wikipedia’s 422 language editions, and makes salient information that is million monthly visitors [12] from accessing most of the unique to each language as well as that which is shared information on the site. more widely. We detail solutions to numerous front-end and algorithmic challenges inherent to providing users with In this paper, we present Omnipedia, a system that attempts a multilingual Wikipedia experience. These include to remedy this situation at a large scale. It reduces the silo visualizing content in a language-neutral way and aligning effect by providing users with structured access in their data in the face of diverse information organization native language to over 7.5 million concepts from up to 25 strategies. We present a study of Omnipedia that language editions of Wikipedia. At the same time, it characterizes how people interact with information using a highlights similarities and differences between each of the multilingual lens. -
Title of Thesis: ABSTRACT CLASSIFYING BIAS
ABSTRACT Title of Thesis: CLASSIFYING BIAS IN LARGE MULTILINGUAL CORPORA VIA CROWDSOURCING AND TOPIC MODELING Team BIASES: Brianna Caljean, Katherine Calvert, Ashley Chang, Elliot Frank, Rosana Garay Jáuregui, Geoffrey Palo, Ryan Rinker, Gareth Weakly, Nicolette Wolfrey, William Zhang Thesis Directed By: Dr. David Zajic, Ph.D. Our project extends previous algorithmic approaches to finding bias in large text corpora. We used multilingual topic modeling to examine language-specific bias in the English, Spanish, and Russian versions of Wikipedia. In particular, we placed Spanish articles discussing the Cold War on a Russian-English viewpoint spectrum based on similarity in topic distribution. We then crowdsourced human annotations of Spanish Wikipedia articles for comparison to the topic model. Our hypothesis was that human annotators and topic modeling algorithms would provide correlated results for bias. However, that was not the case. Our annotators indicated that humans were more perceptive of sentiment in article text than topic distribution, which suggests that our classifier provides a different perspective on a text’s bias. CLASSIFYING BIAS IN LARGE MULTILINGUAL CORPORA VIA CROWDSOURCING AND TOPIC MODELING by Team BIASES: Brianna Caljean, Katherine Calvert, Ashley Chang, Elliot Frank, Rosana Garay Jáuregui, Geoffrey Palo, Ryan Rinker, Gareth Weakly, Nicolette Wolfrey, William Zhang Thesis submitted in partial fulfillment of the requirements of the Gemstone Honors Program, University of Maryland, 2018 Advisory Committee: Dr. David Zajic, Chair Dr. Brian Butler Dr. Marine Carpuat Dr. Melanie Kill Dr. Philip Resnik Mr. Ed Summers © Copyright by Team BIASES: Brianna Caljean, Katherine Calvert, Ashley Chang, Elliot Frank, Rosana Garay Jáuregui, Geoffrey Palo, Ryan Rinker, Gareth Weakly, Nicolette Wolfrey, William Zhang 2018 Acknowledgements We would like to express our sincerest gratitude to our mentor, Dr. -
Iclab: a Global, Longitudinal Internet Censorship Measurement Platform
ICLab: A Global, Longitudinal Internet Censorship Measurement Platform Arian Akhavan Niaki∗y Shinyoung Cho∗yz Zachary Weinberg∗x Nguyen Phong Hoangz Abbas Razaghpanahz Nicolas Christinx Phillipa Gilly yUniversity of Massachusetts, Amherst zStony Brook University xCarnegie Mellon University {arian, shicho, phillipa}@cs.umass.edu {shicho, nghoang, arazaghpanah}@cs.stonybrook.edu {zackw, nicolasc}@cmu.edu Abstract—Researchers have studied Internet censorship for remains elusive. We highlight three key challenges that must nearly as long as attempts to censor contents have taken place. be addressed to make progress in this space: Most studies have however been limited to a short period of time and/or a few countries; the few exceptions have traded off detail Challenge 1: Access to Vantage Points. With few ex- for breadth of coverage. Collecting enough data for a compre- ceptions,1 measuring Internet censorship requires access to hensive, global, longitudinal perspective remains challenging. “vantage point” hosts within the region of interest. In this work, we present ICLab, an Internet measurement The simplest way to obtain vantage points is to recruit platform specialized for censorship research. It achieves a new balance between breadth of coverage and detail of measurements, volunteers [37], [43], [73], [80]. Volunteers can run software by using commercial VPNs as vantage points distributed around that performs arbitrary network measurements from each the world. ICLab has been operated continuously since late vantage point, but recruiting more than a few volunteers per 2016. It can currently detect DNS manipulation and TCP packet country and retaining them for long periods is difficult. Further, injection, and overt “block pages” however they are delivered. -
End of News:Internet Censorship in Turkey
https://www.freewebturkey.com/end-of-news End of news: Internet censorship in Turkey This report was published as part of the Free Web Turkey project carried out by the Media and Law Studies Association between November 2019 and October 2020. http://www.freewebturkey.com | http://www.mlsaturkey.com About MLSA and Free Web Turkey The Media and Law Studies Association (MLSA) was founded in 2017 and its main field of activity is of- fering legal protection to journalists and people tried in freedom of expression cases. As the MLSA, we aim to provide guidance to websites, media organizations and all content producers facing censorship in digital media on methods of coping with censorship, offering them legal consultancy, tools to avoid censorship and a set of internet services that would ease their efforts within the scope of the Free Web Turkey project, which we have been conducting in the field of internet freedom for a year. Besides, we bring together groups working in the field of digital freedoms and freedom of expression to organize panels, roundtable discussions, publish articles, and conduct training programs for content producers to raise awareness against censorship. Another goal of our project is to organize the network of communication and solidarity between institutions, which is one of the most essential components in combating digital censorship. To this end, we try to keep an up-to- date list of blocked URLs and create a database so that we can run a joint and more powerful campaign against censorship. While doing all these, we aim to protect the freedom of expression in the law, the Constitution and international conventions, and to exercise this right effectively. -
Florida State University Libraries
)ORULGD6WDWH8QLYHUVLW\/LEUDULHV 2020 Wiki-Donna: A Contribution to a More Gender-Balanced History of Italian Literature Online Zoe D'Alessandro Follow this and additional works at DigiNole: FSU's Digital Repository. For more information, please contact [email protected] THE FLORIDA STATE UNIVERSITY COLLEGE OF ARTS & SCIENCES WIKI-DONNA: A CONTRIBUTION TO A MORE GENDER-BALANCED HISTORY OF ITALIAN LITERATURE ONLINE By ZOE D’ALESSANDRO A Thesis submitted to the Department of Modern Languages and Linguistics in partial fulfillment of the requirements for graduation with Honors in the Major Degree Awarded: Spring, 2020 The members of the Defense Committee approve the thesis of Zoe D’Alessandro defended on April 20, 2020. Dr. Silvia Valisa Thesis Director Dr. Celia Caputi Outside Committee Member Dr. Elizabeth Coggeshall Committee Member Introduction Last year I was reading Una donna (1906) by Sibilla Aleramo, one of the most important works in Italian modern literature and among the very first explicitly feminist works in the Italian language. Wanting to know more about it, I looked it up on Wikipedia. Although there exists a full entry in the Italian Wikipedia (consisting of a plot summary, publishing information, and external links), the corresponding page in the English Wikipedia consisted only of a short quote derived from a book devoted to gender studies, but that did not address that specific work in great detail. As in-depth and ubiquitous as Wikipedia usually is, I had never thought a work as important as this wouldn’t have its own page. This discovery prompted the question: if this page hadn’t been translated, what else was missing? And was this true of every entry for books across languages, or more so for women writers? My work in expanding the entry for Una donna was the beginning of my exploration into the presence of Italian women writers in the Italian and English Wikipedias, and how it relates back to canon, Wikipedia, and gender studies. -
Parallel Creation of Gigaword Corpora for Medium Density Languages – an Interim Report
Parallel creation of gigaword corpora for medium density languages – an interim report Peter´ Halacsy,´ Andras´ Kornai, Peter´ Nemeth,´ Daniel´ Varga Budapest University of Technology Media Research Center H-1111 Budapest Stoczek u 2 {hp,kornai,pnemeth,daniel}@mokk.bme.hu Abstract For increased speed in developing gigaword language resources for medium resource density languages we integrated several FOSS tools in the HUN* toolkit. While the speed and efficiency of the resulting pipeline has surpassed our expectations, our experience in developing LDC-style resource packages for Uzbek and Kurdish makes clear that neither the data collection nor the subsequent processing stages can be fully automated. 1. Introduction pages (http://technorati.com/weblog/2007/ So far only a select few languages have been fully in- 04/328.html, April 2007) as a proxy for widely tegrated in the bloodstream of modern communications, available material. While the picture is somewhat distorted commerce, research, and education. Most research, devel- by artificial languages (Esperanto, Volapuk,¨ Basic En- opment, and even the language- and area-specific profes- glish) which have enthusiastic wikipedia communities but sional societies in computational linguistics (CL), natural relatively few webpages elsewhere, and by regional lan- language processing (NLP), and information retrieval (IR), guages in the European Union (Catalan, Galician, Basque, target English, the FIGS languages (French, Italian, Ger- Luxembourgish, Breton, Welsh, Lombard, Piedmontese, man, Spanish), -
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. -
Flags and Banners
Flags and Banners A Wikipedia Compilation by Michael A. Linton Contents 1 Flag 1 1.1 History ................................................. 2 1.2 National flags ............................................. 4 1.2.1 Civil flags ........................................... 8 1.2.2 War flags ........................................... 8 1.2.3 International flags ....................................... 8 1.3 At sea ................................................. 8 1.4 Shapes and designs .......................................... 9 1.4.1 Vertical flags ......................................... 12 1.5 Religious flags ............................................. 13 1.6 Linguistic flags ............................................. 13 1.7 In sports ................................................ 16 1.8 Diplomatic flags ............................................ 18 1.9 In politics ............................................... 18 1.10 Vehicle flags .............................................. 18 1.11 Swimming flags ............................................ 19 1.12 Railway flags .............................................. 20 1.13 Flagpoles ............................................... 21 1.13.1 Record heights ........................................ 21 1.13.2 Design ............................................. 21 1.14 Hoisting the flag ............................................ 21 1.15 Flags and communication ....................................... 21 1.16 Flapping ................................................ 23 1.17 See also ............................................... -
Detecting Undisclosed Paid Editing in Wikipedia
Detecting Undisclosed Paid Editing in Wikipedia Nikesh Joshi, Francesca Spezzano, Mayson Green, and Elijah Hill Computer Science Department, Boise State University Boise, Idaho, USA [email protected] {nikeshjoshi,maysongreen,elijahhill}@u.boisestate.edu ABSTRACT 1 INTRODUCTION Wikipedia, the free and open-collaboration based online ency- Wikipedia is the free online encyclopedia based on the principle clopedia, has millions of pages that are maintained by thousands of of open collaboration; for the people by the people. Anyone can volunteer editors. As per Wikipedia’s fundamental principles, pages add and edit almost any article or page. However, volunteers should on Wikipedia are written with a neutral point of view and main- follow a set of guidelines when editing Wikipedia. The purpose tained by volunteer editors for free with well-defned guidelines in of Wikipedia is “to provide the public with articles that summa- order to avoid or disclose any confict of interest. However, there rize accepted knowledge, written neutrally and sourced reliably” 1 have been several known incidents where editors intentionally vio- and the encyclopedia should not be considered as a platform for late such guidelines in order to get paid (or even extort money) for advertising and self-promotion. Wikipedia’s guidelines strongly maintaining promotional spam articles without disclosing such. discourage any form of confict-of-interest (COI) editing and require In this paper, we address for the frst time the problem of identi- editors to disclose any COI contribution. Paid editing is a form of fying undisclosed paid articles in Wikipedia. We propose a machine COI editing and refers to editing Wikipedia (in the majority of the learning-based framework using a set of features based on both cases for promotional purposes) in exchange for compensation. -
Post-Digital Cultures of the Far Right
Maik Fielitz, Nick Thurston (eds.) Post-Digital Cultures of the Far Right Political Science | Volume 71 Maik Fielitz, Nick Thurston (eds.) Post-Digital Cultures of the Far Right Online Actions and Offline Consequences in Europe and the US With kind support of Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Na- tionalbibliografie; detailed bibliographic data are available in the Internet at http://dnb.d-nb.de This work is licensed under the Creative Commons Attribution-NonCommercial-No- Derivatives 4.0 (BY-NC-ND) which means that the text may be used for non-commer- cial purposes, provided credit is given to the author. For details go to http://creativecommons.org/licenses/by-nc-nd/4.0/ To create an adaptation, translation, or derivative of the original work and for com- mercial use, further permission is required and can be obtained by contacting [email protected] Creative Commons license terms for re-use do not apply to any content (such as graphs, figures, photos, excerpts, etc.) not original to the Open Access publication and further permission may be required from the rights holder. The obligation to research and clear permission lies solely with the party re-using the material. © 2019 transcript Verlag, Bielefeld Cover layout: Kordula Röckenhaus, Bielefeld Typeset by Alexander Masch, Bielefeld Printed by Majuskel Medienproduktion GmbH, Wetzlar Print-ISBN 978-3-8376-4670-2 PDF-ISBN 978-3-8394-4670-6 https://doi.org/10.14361/9783839446706 Contents Introduction | 7 Stephen Albrecht, Maik Fielitz and Nick Thurston ANALYZING Understanding the Alt-Right.