How Wikipedia Can Overcome the Great Firewall of China
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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. -
Playing Prejudice: the Impact of Game-Play on Attributions of Gender and Racial Bias
Playing Prejudice: The Impact of Game-Play on Attributions of Gender and Racial Bias Jessica Hammer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Jessica Hammer All rights reserved ABSTRACT Playing Prejudice: The Impact of Game-Play on Attributions of Gender and Racial Bias Jessica Hammer This dissertation explores new possibilities for changing Americans' theories about racism and sexism. Popular American rhetorics of discrimination, and learners' naïve models, are focused on individual agents' role in creating bias. These theories do not encompass the systemic and structural aspects of discrimination in American society. When learners can think systemically as well as agentically about bias, they become more likely to support systemic as well as individual remedies. However, shifting from an agentic to a systemic model of discrimination is both cognitively and emotionally challenging. To tackle this difficult task, this dissertation brings together the literature on prejudice reduction and conceptual change to propose using games as an entertainment-based intervention to change players' attribution styles around sexism and racism, as well as their attitudes about the same issues. “Playable model – anomalous data” theory proposes that games can model complex systems of bias, while instantiating learning mechanics that help players confront the limits of their existing models. The web-based -
Internet Filtering: the Politics and Mechanisms of Control
2 Internet Filtering: The Politics and Mechanisms of Control Jonathan Zittrain and John Palfrey It seems hard to believe that a free, online encyclopedia that anyone can edit at any time could matter much to anyone. But just as a bee can fly despite its awkward physiognomy, Wikipedia has become wildly popular and enormously influential despite its unusual format. The topics that Wikipedians write about range more broadly than any other encyclopedia known to humankind. It has more than 4.6 million articles comprising more than a billion words in two hundred languages.1 Many Google search queries will lead to a Wikipedia page among the top search results. Articles in Wikipedia cover the Tiananmen Square pro- tests of 1989, the Dalai Lama, the International Tibet Independence Movement, and the Tai- wan independence movement. Appearing both in the English and the Chinese language versions of Wikipedia—each independently written—these articles have been written to speak from what Wikipedia calls a ‘‘neutral point of view.’’2 The Wikipedians’ point of view on some topics probably does not seem so neutral to the Chinese authorities. Wikipedia has grown so influential, in fact, that it has attracted the attention of China’s cen- sors at least three times between 2004 and 2006.3 The blocking and unblocking of Wikipedia in China—as with all other filtering in China, with- out announcement or acknowledgment—might also be grounded in a fear of the communal, critical process that Wikipedia represents. The purpose of Wikipedia is ‘‘to create and distrib- ute a multilingual free encyclopedia of the highest quality to every single person on the planet in their own language,’’4 and the means of creating it is through engagement of the public at large to contribute what it knows and to debate in earnest where beliefs differ, offering sources and arguments in quasiacademic style. -
Electronic Frontier Foundation November 9, 2018
Before the Department of Commerce National Telecommunications and Information Administration Developing the Administration’s Approach to Consumer Privacy Docket No. 180821780-8780-01 Comments of Electronic Frontier Foundation November 9, 2018 Submitted by: India McKinney Electronic Frontier Foundation 815 Eddy Street San Francisco, CA 94109 USA Telephone: (415) 436-9333 ext. 175 [email protected] For many years, EFF has urged technology companies and legislators to do a better job of protecting the privacy of technology users and other members of the public. We hoped the companies, who have spent the last decade collecting new and increasingly detailed points of information from their customers, would realize the importance of implementing meaningful privacy protections. But this year’s Cambridge Analytica scandal, following on the heels of many others, was the last straw. Corporations are willfully failing to respect the privacy of technology users, and we need new approaches to give them real incentives to do better—and that includes updating our privacy laws. EFF welcomes the opportunity to work with the Department of Commerce in crafting the federal government’s position on consumer privacy. The Request for Comment published in the Federal Register identifies seven main areas of discussion: Transparency, Control, Reasonable Minimization, Security, Access and Correction, Risk Management, and Accountability. These discussion points have been thoroughly analyzed by academics over the past decades, leading to recommendations like the Fair -
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. -
ALGORITHMIC BIAS EXPLAINED How Automated Decision-Making Becomes Automated Discrimination
ALGORITHMIC BIAS EXPLAINED How Automated Decision-Making Becomes Automated Discrimination Algorithmic Bias Explained | 1 Table of Contents Introduction 3 • What Are Algorithms and How Do They Work? • What Is Algorithmic Bias and Why Does it Matter? • Is Algorithmic Bias Illegal? • Where Does Algorithmic Bias Come From? Algorithmic Bias in Healthcare 10 Algorithmic Bias in Employment 12 Algorithmic Bias in Government Programs 14 Algorithmic BIas in Education 16 Algorithmic Bias in Credit and Finance 18 Algorithmic Bias in Housing and Development 21 Algorithmic BIas in Everything Else: Price Optimization Algorithms 23 Recommendations for Fixing Algorithmic Bias 26 • Algorithmic Transparency and Accountability • Race-Conscious Algorithms • Algorithmic Greenlining Conclusion 32 Introduction Over the last decade, algorithms have replaced decision-makers at all levels of society. Judges, doctors and hiring managers are shifting their responsibilities onto powerful algorithms that promise more data-driven, efficient, accurate and fairer decision-making. However, poorly designed algorithms threaten to amplify systemic racism by reproducing patterns of discrimination and bias that are found in the data algorithms use to learn and make decisions. “We find it important to state that the benefits of any technology should be felt by all of us. Too often, the challenges presented by new technology spell out yet another tale of racism, sexism, gender inequality, ableism and lack of consent within digital 1 culture.” —Mimi Onuoha and Mother Cyborg, authors, “A People’s Guide to A.I.” The goal of this report is to help advocates and policymakers develop a baseline understanding of algorithmic bias and its impact as it relates to socioeconomic opportunity across multiple sectors. -
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. -
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. -
An Analysis of Contributions to Wikipedia from Tor
Are anonymity-seekers just like everybody else? An analysis of contributions to Wikipedia from Tor Chau Tran Kaylea Champion Andrea Forte Department of Computer Science & Engineering Department of Communication College of Computing & Informatics New York University University of Washington Drexel University New York, USA Seatle, USA Philadelphia, USA [email protected] [email protected] [email protected] Benjamin Mako Hill Rachel Greenstadt Department of Communication Department of Computer Science & Engineering University of Washington New York University Seatle, USA New York, USA [email protected] [email protected] Abstract—User-generated content sites routinely block contri- butions from users of privacy-enhancing proxies like Tor because of a perception that proxies are a source of vandalism, spam, and abuse. Although these blocks might be effective, collateral damage in the form of unrealized valuable contributions from anonymity seekers is invisible. One of the largest and most important user-generated content sites, Wikipedia, has attempted to block contributions from Tor users since as early as 2005. We demonstrate that these blocks have been imperfect and that thousands of attempts to edit on Wikipedia through Tor have been successful. We draw upon several data sources and analytical techniques to measure and describe the history of Tor editing on Wikipedia over time and to compare contributions from Tor users to those from other groups of Wikipedia users. Fig. 1. Screenshot of the page a user is shown when they attempt to edit the Our analysis suggests that although Tor users who slip through Wikipedia article on “Privacy” while using Tor. Wikipedia’s ban contribute content that is more likely to be reverted and to revert others, their contributions are otherwise similar in quality to those from other unregistered participants and to the initial contributions of registered users. -
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. -
Chevron's Abusive Litigation in Ecuador
Rainforest Chernobyl Revisited† The Clash of Human Rights and BIT Investor Claims: Chevron’s Abusive Litigation in Ecuador’s Amazon by Steven Donziger,* Laura Garr & Aaron Marr Page** a marathon environmental litigation: Seventeen yearS anD Counting he last time the environmental lawsuit Aguinda v. ChevronTexaco was discussed in these pages, the defen- Tdant Chevron Corporation1 had just won a forum non conveniens dismissal of the case from a U.S. federal court to Ecuador after nine years of litigation. Filed in 1993, the lawsuit alleged that Chevron’s predecessor company, Texaco, while it exclusively operated several oil fields in Ecuador’s Amazon from 1964 to 1990, deliberately dumped billions of gallons of toxic waste into the rainforest to cut costs and abandoned more than 900 large unlined waste pits that leach toxins into soils and groundwater. The suit contended that the contamination poisoned an area the size of Rhode Island, created a cancer epi- demic, and decimated indigenous groups. During the U.S. stage of the litigation, Chevron submitted fourteen sworn affidavits attesting to the fairness and adequacy of Ecuador’s courts. The company also drafted a letter that was By Lou Dematteis/Redux. Steven Donziger, attorney for the affected communities, speaks with signed by Ecuador’s then ambassador to the United States, a Huaorani women outside the Superior Court at the start of the Chevron former Chevron lawyer, asking the U.S. court to send the case trial on October 21, 2003 in Lago Agrio in the Ecuadoran Amazon. to Ecuador.2 Representative of Chevron’s position was the sworn statement from Dr.