How to Conduct Wikipedia Editing Training
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A Survey of Orthographic Information in Machine Translation 3
Machine Translation Journal manuscript No. (will be inserted by the editor) A Survey of Orthographic Information in Machine Translation Bharathi Raja Chakravarthi1 ⋅ Priya Rani 1 ⋅ Mihael Arcan2 ⋅ John P. McCrae 1 the date of receipt and acceptance should be inserted later Abstract Machine translation is one of the applications of natural language process- ing which has been explored in different languages. Recently researchers started pay- ing attention towards machine translation for resource-poor languages and closely related languages. A widespread and underlying problem for these machine transla- tion systems is the variation in orthographic conventions which causes many issues to traditional approaches. Two languages written in two different orthographies are not easily comparable, but orthographic information can also be used to improve the machine translation system. This article offers a survey of research regarding orthog- raphy’s influence on machine translation of under-resourced languages. It introduces under-resourced languages in terms of machine translation and how orthographic in- formation can be utilised to improve machine translation. We describe previous work in this area, discussing what underlying assumptions were made, and showing how orthographic knowledge improves the performance of machine translation of under- resourced languages. We discuss different types of machine translation and demon- strate a recent trend that seeks to link orthographic information with well-established machine translation methods. Considerable attention is given to current efforts of cog- nates information at different levels of machine translation and the lessons that can Bharathi Raja Chakravarthi [email protected] Priya Rani [email protected] Mihael Arcan [email protected] John P. -
Wikipedia and Intermediary Immunity: Supporting Sturdy Crowd Systems for Producing Reliable Information Jacob Rogers Abstract
THE YALE LAW JOURNAL FORUM O CTOBER 9 , 2017 Wikipedia and Intermediary Immunity: Supporting Sturdy Crowd Systems for Producing Reliable Information Jacob Rogers abstract. The problem of fake news impacts a massive online ecosystem of individuals and organizations creating, sharing, and disseminating content around the world. One effective ap- proach to addressing false information lies in monitoring such information through an active, engaged volunteer community. Wikipedia, as one of the largest online volunteer contributor communities, presents one example of this approach. This Essay argues that the existing legal framework protecting intermediary companies in the United States empowers the Wikipedia community to ensure that information is accurate and well-sourced. The Essay further argues that current legal efforts to weaken these protections, in response to the “fake news” problem, are likely to create perverse incentives that will harm volunteer engagement and confuse the public. Finally, the Essay offers suggestions for other intermediaries beyond Wikipedia to help monitor their content through user community engagement. introduction Wikipedia is well-known as a free online encyclopedia that covers nearly any topic, including both the popular and the incredibly obscure. It is also an encyclopedia that anyone can edit, an example of one of the largest crowd- sourced, user-generated content websites in the world. This user-generated model is supported by the Wikimedia Foundation, which relies on the robust intermediary liability immunity framework of U.S. law to allow the volunteer editor community to work independently. Volunteer engagement on Wikipedia provides an effective framework for combating fake news and false infor- mation. 358 wikipedia and intermediary immunity: supporting sturdy crowd systems for producing reliable information It is perhaps surprising that a project open to public editing could be highly reliable. -
Wikipedia Ahead
Caution: Wikipedia not might be what you think it is… What is Wikipedia? Wikipedia is an online encyclopedia that is written, updated, rewritten, and edited by registered site users around the world known as “Wikipedians”. The concept of a freely accessible online “work in progress” is known as a “wiki” (Lin, 2004). While it is possible to view the user profile of individual contributors, one of the prime features of a wiki is that the information is collectively owned, shared, and changed by Internet users who have access to that wiki. Wikipedia is accessible to anyone with an Internet connection. Why Wikipedia? The main philosophy behind Wikipedia is that the sum total of the ideas of Internet users are as credible and valid as the published views of experts who have advanced degrees and extensive experience in their field. Like any wiki, Wikipedians do not “own” or assume intellectual property of the ideas and text, as the information is shared or altered by any/all contributors. I’m not sure what you mean…. An example may be most helpful. Consider Wikipedia’s article on global warming. This text has been continually written, edited, and rewritten by hundreds of Internet users around the world over the past few years. When you open and read Wikipedia’s global warming article, you are reading a text that: • is the sum of all the contributions to this article until that moment. Explanation: The information in the article, in terms of both the content and language, will likely change in the next few hours, days, or months as Wikipedias continue to contribute to/modify the article. -
Decentralization in Wikipedia Governance
Decentralization in Wikipedia Governance Andrea Forte1, Vanessa Larco2 and Amy Bruckman1 1GVU Center, College of Computing, Georgia Institute of Technology {aforte, asb}@cc.gatech.edu 2Microsoft [email protected] This is a preprint version of the journal article: Forte, Andrea, Vanessa Larco and Amy Bruckman. (2009) Decentralization in Wikipedia Governance. Journal of Management Information Systems. 26(1) pp 49-72. Publisher: M.E. Sharp www.mesharpe.com/journals.asp Abstract How does “self-governance” happen in Wikipedia? Through in-depth interviews with twenty individuals who have held a variety of responsibilities in the English-language Wikipedia, we obtained rich descriptions of how various forces produce and regulate social structures on the site. Our analysis describes Wikipedia as an organization with highly refined policies, norms, and a technological architecture that supports organizational ideals of consensus building and discussion. We describe how governance on the site is becoming increasingly decentralized as the community grows and how this is predicted by theories of commons-based governance developed in offline contexts. We also briefly examine local governance structures called WikiProjects through the example of WikiProject Military History, one of the oldest and most prolific projects on the site. 1. The Mechanisms of Self-Organization Should a picture of a big, hairy tarantula appear in an encyclopedia article about arachnophobia? Does it illustrate the point, or just frighten potential readers? Reasonable people might disagree on this question. In a freely editable site like Wikipedia, anyone can add the photo, and someone else can remove it. And someone can add it back, and the process continues. -
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. -
State of Wikimedia Communities of India
State of Wikimedia Communities of India Assamese http://as.wikipedia.org State of Assamese Wikipedia RISE OF ASSAMESE WIKIPEDIA Number of edits and internal links EDITS PER MONTH INTERNAL LINKS GROWTH OF ASSAMESE WIKIPEDIA Number of good Date Articles January 2010 263 December 2012 301 (around 3 articles per month) November 2011 742 (around 40 articles per month) Future Plans Awareness Sessions and Wiki Academy Workshops in Universities of Assam. Conduct Assamese Editing Workshops to groom writers to write in Assamese. Future Plans Awareness Sessions and Wiki Academy Workshops in Universities of Assam. Conduct Assamese Editing Workshops to groom writers to write in Assamese. THANK YOU Bengali বাংলা উইকিপিডিয়া Bengali Wikipedia http://bn.wikipedia.org/ By Bengali Wikipedia community Bengali Language • 6th most spoken language • 230 million speakers Bengali Language • National language of Bangladesh • Official language of India • Official language in Sierra Leone Bengali Wikipedia • Started in 2004 • 22,000 articles • 2,500 page views per month • 150 active editors Bengali Wikipedia • Monthly meet ups • W10 anniversary • Women’s Wikipedia workshop Wikimedia Bangladesh local chapter approved in 2011 by Wikimedia Foundation English State of WikiProject India on ENGLISH WIKIPEDIA ● One of the largest Indian Wikipedias. ● WikiProject started on 11 July 2006 by GaneshK, an NRI. ● Number of article:89,874 articles. (Excludes those that are not tagged with the WikiProject banner) ● Editors – 465 (active) ● Featured content : FAs - 55, FLs - 20, A class – 2, GAs – 163. BASIC STATISTICS ● B class – 1188 ● C class – 801 ● Start – 10,931 ● Stub – 43,666 ● Unassessed for quality – 20,875 ● Unknown importance – 61,061 ● Cleanup tags – 43,080 articles & 71,415 tags BASIC STATISTICS ● Diversity of opinion ● Lack of reliable sources ● Indic sources „lost in translation“ ● Editor skills need to be upgraded ● Lack of leadership ● Lack of coordinated activities ● …. -
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. -
Multilingual Ranking of Wikipedia Articles with Quality and Popularity Assessment in Different Topics
computers Article Multilingual Ranking of Wikipedia Articles with Quality and Popularity Assessment in Different Topics Włodzimierz Lewoniewski * , Krzysztof W˛ecel and Witold Abramowicz Department of Information Systems, Pozna´nUniversity of Economics and Business, 61-875 Pozna´n,Poland * Correspondence: [email protected]; Tel.: +48-(61)-639-27-93 Received: 10 May 2019; Accepted: 13 August 2019; Published: 14 August 2019 Abstract: On Wikipedia, articles about various topics can be created and edited independently in each language version. Therefore, the quality of information about the same topic depends on the language. Any interested user can improve an article and that improvement may depend on the popularity of the article. The goal of this study is to show what topics are best represented in different language versions of Wikipedia using results of quality assessment for over 39 million articles in 55 languages. In this paper, we also analyze how popular selected topics are among readers and authors in various languages. We used two approaches to assign articles to various topics. First, we selected 27 main multilingual categories and analyzed all their connections with sub-categories based on information extracted from over 10 million categories in 55 language versions. To classify the articles to one of the 27 main categories, we took into account over 400 million links from articles to over 10 million categories and over 26 million links between categories. In the second approach, we used data from DBpedia and Wikidata. We also showed how the results of the study can be used to build local and global rankings of the Wikipedia content. -
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. -
Group Identification, Goal Setting and Social Modeling in Directing Online
Organizing without Formal Organization: Group Identification, Goal Setting and Social Modeling in Directing Online Production Haiyi Zhu, Robert Kraut, Aniket Kittur Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA15213 {haiyiz, robert.kraut, nkittur}@cs.cmu.edu ABSTRACT INTRODUCTION A challenge for many online production communities is to Online production communities are becoming increasingly direct their members to accomplish tasks that are important important in creating innovative products in the networked to the group, even when these tasks may not match world. These organizations have successfully aggregated individual members’ interests. Here we investigate how the efforts of millions of volunteers to produce complex combining group identification and direction setting can artifacts such as GNU/Linux and Wikipedia. Currently most motivate volunteers in online communities to accomplish large online projects primarily rely on a paradigm of self- tasks important to the success of the group as a whole. We direction in which contributors work primarily on the tasks hypothesize that group identity, the perception of belonging they are interested in. This paradigm provides a number of to a group, triggers in-group favoritism; and direction benefits. Contributors are motivated to work on the tasks in setting (including explicit direction from group goals and which they are intrinsically interested in and are likely to implicit direction from role models) focuses people’s choose tasks in which they already have some expertise [4]. group-oriented motivation towards the group’s important However, this approach breaks down when there are tasks. We tested our hypotheses in the context of conflicts between the interests of the contributors and the Wikipedia's Collaborations of the Week (COTW), a group interests of the project as a whole. -
© 2020 Xiaoman Pan CROSS-LINGUAL ENTITY EXTRACTION and LINKING for 300 LANGUAGES
© 2020 Xiaoman Pan CROSS-LINGUAL ENTITY EXTRACTION AND LINKING FOR 300 LANGUAGES BY XIAOMAN PAN DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science in the Graduate College of the University of Illinois at Urbana-Champaign, 2020 Urbana, Illinois Doctoral Committee: Dr. Heng Ji, Chair Dr. Jiawei Han Dr. Hanghang Tong Dr. Kevin Knight ABSTRACT Information provided in languages which people can understand saves lives in crises. For example, language barrier was one of the main difficulties faced by humanitarian workers responding to the Ebola crisis in 2014. We propose to break language barriers by extracting information (e.g., entities) from a massive variety of languages and ground the information into an existing Knowledge Base (KB) which is accessible to a user in their own language (e.g., a reporter from the World Health Organization who speaks English only). The ambitious goal of this thesis is to develop a Cross-lingual Entity Extraction and Linking framework for 1,000 fine-grained entity types and 300 languages that exist in Wikipedia. Given a document in any of these languages, our framework is able to identify entity name mentions, assign a fine-grained type to each mention, and link it to an English KB if it is linkable. Traditional entity linking methods rely on costly human annotated data to train supervised learning-to-rank models to select the best candidate entity for each mention. In contrast, we propose a novel unsupervised represent-and-compare approach that can accurately capture the semantic meaning representation of each mention, and directly compare its representation with the representation of each candidate entity in the target KB. -
How to Contribute Climate Change Information to Wikipedia : a Guide
HOW TO CONTRIBUTE CLIMATE CHANGE INFORMATION TO WIKIPEDIA Emma Baker, Lisa McNamara, Beth Mackay, Katharine Vincent; ; © 2021, CDKN This work is licensed under the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/legalcode), which permits unrestricted use, distribution, and reproduction, provided the original work is properly credited. Cette œuvre est mise à disposition selon les termes de la licence Creative Commons Attribution (https://creativecommons.org/licenses/by/4.0/legalcode), qui permet l’utilisation, la distribution et la reproduction sans restriction, pourvu que le mérite de la création originale soit adéquatement reconnu. IDRC Grant/ Subvention du CRDI: 108754-001-CDKN knowledge accelerator for climate compatible development How to contribute climate change information to Wikipedia A guide for researchers, practitioners and communicators Contents About this guide .................................................................................................................................................... 5 1 Why Wikipedia is an important tool to communicate climate change information .................................................................................................................................. 7 1.1 Enhancing the quality of online climate change information ............................................. 8 1.2 Sharing your work more widely ......................................................................................................8 1.3 Why researchers should