The Most Controversial Topics in Wikipedia: a Multilingual and Geographical Analysis
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Wikipedia Edit-A-Thons and Editor Experience: Lessons from a Participatory Observation
Aalborg Universitet Wikipedia Edit-a-thons and Editor Experience: Lessons from a Participatory Observation Gluza, Wioletta; Turaj, Izabela ; Meier, Florian Maximilian Published in: Proceeding of 17th International Symposium on Open Collaboration (OpenSym2021) Publication date: 2021 Link to publication from Aalborg University Citation for published version (APA): Gluza, W., Turaj, I., & Meier, F. M. (Accepted/In press). Wikipedia Edit-a-thons and Editor Experience: Lessons from a Participatory Observation. In Proceeding of 17th International Symposium on Open Collaboration (OpenSym2021) General rights 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 ? Take down policy If you believe that this document breaches copyright please contact us at [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Wikipedia Edit-a-thons and Editor Experience: Lessons from a Participatory Observation WIOLETTA GLUZA, Aalborg University Copenhagen, Denmark IZABELA ANNA TURAJ, Aalborg University Copenhagen, Denmark FLORIAN MEIER, Aalborg University Copenhagen, Denmark Wikipedia is one of the most important sources of encyclopedic knowledge and among the most visited websites on the internet. -
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. -
RASLAN 2017 Recent Advances in Slavonic Natural Language Processing
RASLAN 2017 Recent Advances in Slavonic Natural Language Processing A. Horák, P. Rychlý, A. Rambousek (Eds.) RASLAN 2017 Recent Advances in Slavonic Natural Language Processing Eleventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2017 Karlova Studánka, Czech Republic, December 1–3, 2017 Proceedings Tribun EU 2017 Proceedings Editors Aleš Horák Faculty of Informatics, Masaryk University Department of Information Technologies Botanická 68a CZ-602 00 Brno, Czech Republic Email: [email protected] Pavel Rychlý Faculty of Informatics, Masaryk University Department of Information Technologies Botanická 68a CZ-602 00 Brno, Czech Republic Email: [email protected] Adam Rambousek Faculty of Informatics, Masaryk University Department of Information Technologies Botanická 68a CZ-602 00 Brno, Czech Republic Email: [email protected] This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the Czech Copyright Law, in its current version, and permission for use must always be obtained from Tribun EU. Violations are liable for prosecution under the Czech Copyright Law. Editors © Aleš Horák, 2017; Pavel Rychlý, 2017; Adam Rambousek, 2017 Typography © Adam Rambousek, 2017 Cover © Petr Sojka, 2010 This edition © Tribun EU, Brno, 2017 ISBN 978-80-263-1340-3 ISSN 2336-4289 Preface This volume contains the Proceedings of the Eleventh Workshop on Recent Advances in Slavonic Natural Language Processing (RASLAN 2017) held on December 1st–3rd 2017 in Karlova Studánka, Sporthotel Kurzovní, Jeseníky, Czech Republic. -
Social Changer Jae-Hee Technology Comfort Level
Social Changer Jae-Hee Technology comfort level AGE: EDUCATION: 27 years old University Low High LOCATION: LANGUAGES: Seoul, South Korea Korean (fluent) Writing comfort level Japanese (proficient) OCCUPATION: English (proficient) Freelance graphic designer Low High Macbook Pro iPad iPhone 6S PRIMARY USE: Graphic design work, PRIMARY USE: Reading, looking for PRIMARY USE: Calling, messaging maintaining her website, writing, inspiration for her work, and quick friends on Kakao Talk, Twitter editing Wikipedia internet browsing when she’s not at home Background Jae-Hee graduated from university two years ago Japanese. While in university, she took a class on Experience Goals and currently works as a freelance graphic de- design and sustainability and became interested • To freely share her opinions and signer. She lives in the suburbs of Seoul, with her in environmental issues. Now she volunteers for knowledge without conflict or rebuke, parents and younger sister. In her spare time, she an environmental advocacy non-profit which ed- like she does elsewhere online works on her digital art and photography, which ucates people about living a sustainable lifestyle, she publishes on her personal website, through and shares similar lifestyle tips on her personal End Goals WordPress. She loves reading, particularly fantasy blog. and science fiction stories, in both Korean and • To raise awareness on environmental issues • To collaborate with other Tech Habits environmentalists She first started using a computer in grade school, environmental groups. She is well-known by her and got her first smartphone in high school. She online username, “jigu”. She learned basic HTML Challenges uses social media avidly, particularly Twitter to to run her website, and uses Adobe software for share her work and writing, and to follow other her graphic design and art. -
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 ............................................... -
Natural Language Processing for Similar Languages, Varieties, and Dialects: a Survey
Natural Language Engineering (2020), 26, pp. 595–612 doi:10.1017/S1351324920000492 SURVEY PAPER Natural language processing for similar languages, varieties, and dialects: A survey Marcos Zampieri 1,∗ Preslav Nakov 2 and Yves Scherrer 3 1Rochester Institute of Technology, USA, 2Qatar Computing Research Institute, HBKU, Qatar and 3University of Helsinki, Finland ∗ Corresponding author. E-mail: [email protected] Abstract There has been a lot of recent interest in the natural language processing (NLP) community in the com- putational processing of language varieties and dialects, with the aim to improve the performance of applications such as machine translation, speech recognition, and dialogue systems. Here, we attempt to survey this growing field of research, with focus on computational methods for processing similar lan- guages, varieties, and dialects. In particular, we discuss the most important challenges when dealing with diatopic language variation, and we present some of the available datasets, the process of data collection, and the most common data collection strategies used to compile datasets for similar languages, varieties, and dialects. We further present a number of studies on computational methods developed and/or adapted for preprocessing, normalization, part-of-speech tagging, and parsing similar languages, language vari- eties, and dialects. Finally, we discuss relevant applications such as language and dialect identification and machine translation for closely related languages, language varieties, and dialects. Keywords: Dialects; similar languages; language varieties; language identification machine; translation parsing 1. Introduction Variation is intrinsic to human language and it is manifested in different ways. There are four generally accepted dimensions of language variation, namely diaphasic, diastratic, diachronic,and diatopic. -
Wikipedia Matters∗
Wikipedia Matters∗ Marit Hinnosaar† Toomas Hinnosaar‡ Michael Kummer§ Olga Slivko¶ September 29, 2017 Abstract We document a causal impact of online user-generated information on real-world economic outcomes. In particular, we conduct a randomized field experiment to test whether additional content on Wikipedia pages about cities affects tourists’ choices of overnight visits. Our treatment of adding information to Wikipedia increases overnight visits by 9% during the tourist season. The impact comes mostly from improving the shorter and incomplete pages on Wikipedia. These findings highlight the value of content in digital public goods for informing individual choices. JEL: C93, H41, L17, L82, L83, L86 Keywords: field experiment, user-generated content, Wikipedia, tourism industry 1 Introduction Asymmetric information can hinder efficient economic activity. In recent decades, the Internet and new media have enabled greater access to information than ever before. However, the digital divide, language barriers, Internet censorship, and technological con- straints still create inequalities in the amount of accessible information. How much does it matter for economic outcomes? In this paper, we analyze the causal impact of online information on real-world eco- nomic outcomes. In particular, we measure the impact of information on one of the primary economic decisions—consumption. As the source of information, we focus on Wikipedia. It is one of the most important online sources of reference. It is the fifth most ∗We are grateful to Irene Bertschek, Avi Goldfarb, Shane Greenstein, Tobias Kretschmer, Thomas Niebel, Marianne Saam, Greg Veramendi, Joel Waldfogel, and Michael Zhang as well as seminar audiences at the Economics of Network Industries conference in Paris, ZEW Conference on the Economics of ICT, and Advances with Field Experiments 2017 Conference at the University of Chicago for valuable comments. -
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. -
Critical Point of View: a Wikipedia Reader
w ikipedia pedai p edia p Wiki CRITICAL POINT OF VIEW A Wikipedia Reader 2 CRITICAL POINT OF VIEW A Wikipedia Reader CRITICAL POINT OF VIEW 3 Critical Point of View: A Wikipedia Reader Editors: Geert Lovink and Nathaniel Tkacz Editorial Assistance: Ivy Roberts, Morgan Currie Copy-Editing: Cielo Lutino CRITICAL Design: Katja van Stiphout Cover Image: Ayumi Higuchi POINT OF VIEW Printer: Ten Klei Groep, Amsterdam Publisher: Institute of Network Cultures, Amsterdam 2011 A Wikipedia ISBN: 978-90-78146-13-1 Reader EDITED BY Contact GEERT LOVINK AND Institute of Network Cultures NATHANIEL TKACZ phone: +3120 5951866 INC READER #7 fax: +3120 5951840 email: [email protected] web: http://www.networkcultures.org Order a copy of this book by sending an email to: [email protected] A pdf of this publication can be downloaded freely at: http://www.networkcultures.org/publications Join the Critical Point of View mailing list at: http://www.listcultures.org Supported by: The School for Communication and Design at the Amsterdam University of Applied Sciences (Hogeschool van Amsterdam DMCI), the Centre for Internet and Society (CIS) in Bangalore and the Kusuma Trust. Thanks to Johanna Niesyto (University of Siegen), Nishant Shah and Sunil Abraham (CIS Bangalore) Sabine Niederer and Margreet Riphagen (INC Amsterdam) for their valuable input and editorial support. Thanks to Foundation Democracy and Media, Mondriaan Foundation and the Public Library Amsterdam (Openbare Bibliotheek Amsterdam) for supporting the CPOV events in Bangalore, Amsterdam and Leipzig. (http://networkcultures.org/wpmu/cpov/) Special thanks to all the authors for their contributions and to Cielo Lutino, Morgan Currie and Ivy Roberts for their careful copy-editing.