Understanding the Challenges of Collaborative Evidence-Based
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Proceedings of the 11Th International Symposium on Open Collaboration
Proceedings of the 11th International Symposium on Open Collaboration August 19-21, 2015 San Francisco, California, U.S.A. General chair: Dirk Riehle, Friedrich-Alexander University Erlangen-Nürnberg Research track chairs: Kevin Crowston, Syracuse University Carlos Jensen, Oregon State University Carl Lagoze, University of Michigan Ann Majchrzak, University of Southern California Arvind Malhotra, University of North Carolina at Chapel Hill Claudia Müller-Birn, Freie Universität Berlin Gregorio Robles, Universidad Rey Juan Carlos Aaron Shaw, Northwestern University Sponsors: Wikimedia Foundation Google Inc. University of California Berkeley In-cooperation: ACM SIGSOFT ACM SIGWEB Fiscal sponsor: The John Ernest Foundation The Association for Computing Machinery 2 Penn Plaza, Suite 701 New York New York 10121-0701 ACM COPYRIGHT NOTICE. Copyright © 2014 by the Association for Computing Machin- ery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be hon- ored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept., ACM, Inc., fax +1 (212) 869-0481, or [email protected]. For other copying of articles that carry a code at the bottom of the first or last page, copying is permitted provided that the per-copy fee indicated in the code is paid through the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, +1-978-750-8400, +1-978-750- 4470 (fax). -
Using Shape Expressions (Shex) to Share RDF Data Models and to Guide Curation with Rigorous Validation B Katherine Thornton1( ), Harold Solbrig2, Gregory S
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Repositorio Institucional de la Universidad de Oviedo Using Shape Expressions (ShEx) to Share RDF Data Models and to Guide Curation with Rigorous Validation B Katherine Thornton1( ), Harold Solbrig2, Gregory S. Stupp3, Jose Emilio Labra Gayo4, Daniel Mietchen5, Eric Prud’hommeaux6, and Andra Waagmeester7 1 Yale University, New Haven, CT, USA [email protected] 2 Johns Hopkins University, Baltimore, MD, USA [email protected] 3 The Scripps Research Institute, San Diego, CA, USA [email protected] 4 University of Oviedo, Oviedo, Spain [email protected] 5 Data Science Institute, University of Virginia, Charlottesville, VA, USA [email protected] 6 World Wide Web Consortium (W3C), MIT, Cambridge, MA, USA [email protected] 7 Micelio, Antwerpen, Belgium [email protected] Abstract. We discuss Shape Expressions (ShEx), a concise, formal, modeling and validation language for RDF structures. For instance, a Shape Expression could prescribe that subjects in a given RDF graph that fall into the shape “Paper” are expected to have a section called “Abstract”, and any ShEx implementation can confirm whether that is indeed the case for all such subjects within a given graph or subgraph. There are currently five actively maintained ShEx implementations. We discuss how we use the JavaScript, Scala and Python implementa- tions in RDF data validation workflows in distinct, applied contexts. We present examples of how ShEx can be used to model and validate data from two different sources, the domain-specific Fast Healthcare Interop- erability Resources (FHIR) and the domain-generic Wikidata knowledge base, which is the linked database built and maintained by the Wikimedia Foundation as a sister project to Wikipedia. -
Classifying Wikipedia Article Quality with Revision History Networks
Classifying Wikipedia Article Quality With Revision History Networks Narun Raman∗ Nathaniel Sauerberg∗ Carleton College Carleton College [email protected] [email protected] Jonah Fisher Sneha Narayan Carleton College Carleton College [email protected] [email protected] ABSTRACT long been interested in maintaining and investigating the quality We present a novel model for classifying the quality of Wikipedia of its content [4][6][12]. articles based on structural properties of a network representation Editors and WikiProjects typically rely on assessments of article of the article’s revision history. We create revision history networks quality to focus volunteer attention on improving lower quality (an adaptation of Keegan et. al’s article trajectory networks [7]), articles. This has led to multiple efforts to create classifiers that can where nodes correspond to individual editors of an article, and edges predict the quality of a given article [3][4][18]. These classifiers can join the authors of consecutive revisions. Using descriptive statistics assist in providing assessments of article quality at scale, and help generated from these networks, along with general properties like further our understanding of the features that distinguish high and the number of edits and article size, we predict which of six quality low quality Wikipedia articles. classes (Start, Stub, C-Class, B-Class, Good, Featured) articles belong While many Wikipedia article quality classifiers have focused to, attaining a classification accuracy of 49.35% on a stratified sample on assessing quality based on the content of the latest version of of articles. These results suggest that structures of collaboration an article [1, 4, 18], prior work has suggested that high quality arti- underlying the creation of articles, and not just the content of the cles are associated with more intense collaboration among editors article, should be considered for accurate quality classification. -
E-Posters in Academic/Scientific Conferεnces – Guidelines, Comparative Study & New Suggestions
University of the Aegean Department of Product and Systems Design Engineering DISSERTATION: E-POSTERS IN ACADEMIC/SCIENTIFIC CONFERΕNCES – GUIDELINES, COMPARATIVE STUDY & NEW SUGGESTIONS Pissaridi Maria Anastasia 511/2004041 Supervisor: Paraskevas Papanikos Committee Members: Nikolaos Zacharopoulos Maria Simosi Syros, June 2015 DISSERTATION: E-POSTERS IN ACADEMIC/SCIENTIFIC CONFERENCES – GUIDELINES, COMPARATIVE STUDY & NEW SUGGESTIONS Supervisor: Paraskevas Papanikos Committee Members: Nikolaos Zacharopoulos Maria Simosi Pissaridi Maria Anastasia Syros, June 2015 3 ABSTRACT Conferences play a key role in getting people interested in a field together to network and exchange knowledge. The poster presentation is a commonly used format for communicating information within the academic scientific conference sector. Paper posters were the beginning but as technology and the way people work changes, posters have to be developed and implemented in order to achieve successful knowledge transfer. Incorporating aspects of information technology into poster presentations can promote an interactive learning environment for users and counter the current passive nature of poster design as an integrated approach with supplemental material is required to achieve changes in user knowledge, attitude and behaviour. After conducting literature review, research of existing e-poster providers, interviews with 5 of them and a personal evaluation in a real time conference environment results show a gradual turn towards e-posters with the medical sector pioneering. Authors, viewers and organisers embrace this new format, and the features and functions it offers, although objections exist since people have different preferences and the e-poster sector is relatively young, an average of 5 years. Pissaridi Maria Anastasia dpsd04041 4 SUMMARY Η ανάγκη των ανθρώπων να συγκεντρώνονται για να ανταλλάσσουν ιδέες, ευρήματα, έρευνες και απόψεις υπήρχε από τη δημιουργία των πρώτων πόλεων όπου φτιάχνονται με χώρους συγκέντρωσης. -
Articles & Reports
1 Reading & Resource List on Information Literacy Articles & Reports Adegoke, Yemisi. "Like. Share. Kill.: Nigerian police say false information on Facebook is killing people." BBC News. Accessed November 21, 2018. https://www.bbc.co.uk/news/resources/idt- sh/nigeria_fake_news. See how Facebook posts are fueling ethnic violence. ALA Public Programs Office. “News: Fake News: A Library Resource Round-Up.” American Library Association. February 23, 2017. http://www.programminglibrarian.org/articles/fake-news-library-round. ALA Public Programs Office. “Post-Truth: Fake News and a New Era of Information Literacy.” American Library Association. Accessed March 2, 2017. http://www.programminglibrarian.org/learn/post-truth- fake-news-and-new-era-information-literacy. This has a 45-minute webinar by Dr. Nicole A. Cook, University of Illinois School of Information Sciences, which is intended for librarians but is an excellent introduction to fake news. Albright, Jonathan. “The Micro-Propaganda Machine.” Medium. November 4, 2018. https://medium.com/s/the-micro-propaganda-machine/. In a three-part series, Albright critically examines the role of Facebook in spreading lies and propaganda. Allen, Mike. “Machine learning can’g flag false news, new studies show.” Axios. October 15, 2019. ios.com/machine-learning-cant-flag-false-news-55aeb82e-bcbb-4d5c-bfda-1af84c77003b.html. Allsop, Jon. "After 10,000 'false or misleading claims,' are we any better at calling out Trump's lies?" Columbia Journalism Review. April 30, 2019. https://www.cjr.org/the_media_today/trump_fact- check_washington_post.php. Allsop, Jon. “Our polluted information ecosystem.” Columbia Journalism Review. December 11, 2019. https://www.cjr.org/the_media_today/cjr_disinformation_conference.php. Amazeen, Michelle A. -
Wikipedia's Jimmy Wales Has Launched an Alternative to Facebook and Twitter 11/18/19, 8:11 PM
Wikipedia's Jimmy Wales has launched an alternative to Facebook and Twitter 11/18/19, 8:11 PM Wikipedia's Jimmy Wales has launched an alternative to Facebook and Twitter In a nutshell: Hardly anyone would say that social media is good for you, yet billions use it in one form or another (often concurrently) every single day. These platforms make billions of dollars by addicting users and getting them to click ads. One Wikipedia co-founder wants to change that with a new social media site that is supported by the users rather than big advertisers. Wikipedia co-founder Jimmy Wales is launching a social-media website called WT: Social. The platform aims to compete with Facebook and Twitter, except instead of funding it using advertising, Wales is taking a page from the Wikipedia playbook and financing it through user donations. "The business model of social media companies, of pure advertising, is problematic," Wales told Financial Times. "It turns out the huge winner is low-quality content." WT: Social got its start as Wikitribune, a site that published original news stories with the community fact-checking and sub-editing articles. The venture never gained much traction, so Wales is moving it to the new platform with a more social networking focus. "Instead of optimizing our algorithm to addict you and keep you clicking, we will only make money if you voluntarily choose to support us – which means that our goal is not clicks but actually being meaningful to your life." The site will still post articles, but instead of giving priority to content with the most "Likes," its algorithms will list the newest stories first. -
Response to Evan Williams–
Email Interview on June 22, 2017 with Geert Lovink by Davide Nitrosi, Italian journalist with a group of daily papers such as Bologna’s Resto del Carlino, Florence’s Nazione and Milan’s Giorno. Davide Nitrosi: Once Twitter was viewed as a tool of liberation. During the Arab Spring uprisings in the Middle East and the Iran riots before that Twitter was the media of freedom. We thought Internet was against tyranny. Now we see the abuse of social networks. Twitter founder, Evan Williams, said to the New York Times that Twitter’s role in the Trump election was a very bad thing. What’s your response to this article? Geert Lovink: The phrase “The Internet is broken” than Evan has in fact circulated amongst geeks and engineers since 2013/14 in response to the revelations of Edward Snowden (the campaign used to have the http://internetisbroken.org/ website). The slogan refers to the widely felt loss of privacy, caused by what we now call ‘surveillance capitalism’, in which the industrial-surveillance apparatus around the NSA and affiliated secret services broke the collective dream of a public internet in which users were in charge. The inventor of the World Wide Web, Tim-Berners Lee, is playing an important role here, in the background. Or look at Wikitribune, crowdsourcing evidence-based journalism, the latest intiative of Jimmy Wales (Wikipedia). This issue has been a long one in the making. In that sense, the response of EV comes late. We’re now more than half year into the ‘fake news’ meme (that comes from elsewhere anyway, for instance Ukraine). -
Edit Filters on English Wikipedia
You Shall Not Publish: Edit Filters on English Wikipedia Lyudmila Vaseva Claudia Müller-Birn Human-Centered Computing | Freie Universität Berlin Human-Centered Computing | Freie Universität Berlin [email protected] [email protected] Figure 1: Warning Message of an edit filter to inform the editor that their edit is potentially non-constructive. ABSTRACT ACM Reference Format: Ensuring the quality of the content provided in online settings Lyudmila Vaseva and Claudia Müller-Birn. 2020. You Shall Not Publish: is an important challenge today, for example, for social media or Edit Filters on English Wikipedia. In 16th International Symposium on Open Collaboration (OpenSym 2020), August 25–27, 2020, Virtual conference, Spain. news. The Wikipedia community has ensured the high-quality ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3412569.3412580 standards for an online encyclopaedia from the beginning and has built a sophisticated set of automated, semi-automated, and manual 1 INTRODUCTION quality assurance mechanisms over the last fifteen years. The scien- tific community has systematically studied these mechanisms but The public heatedly debated so-called "upload filters" in the context 1 one mechanism has been overlooked — edit filters. Edit filters are of the EU copyright law reform in 2019 . Upload filters are con- syntactic rules that assess incoming edits, file uploads or account ceived as a form of copyright protection. They should check for creations. As opposed to many other quality assurance mechanisms, possible infringements of copyrighted material even before a con- edit filters are effective before a new revision is stored in the online tribution is published online — and the contributions affected can encyclopaedia. -
R. Stuart Geiger Curriculum Vitae September 2021 [email protected] | | @Staeiou | Google Scholar | Github
Geiger CV 1/14 R. Stuart Geiger Curriculum Vitae September 2021 [email protected] | http://stuartgeiger.com | @staeiou | Google Scholar | GitHub Education University of California at Berkeley, School of Information Ph.D., Information Management & Systems, designated emphasis in New Media December 2015 Georgetown University M.A., Communication, Culture, and Technology May 2009 University of Texas at Austin B.A., Humanities Honors May 2007 Employment University of California at San Diego Assistant Professor, Dept of Communication & Halıcıoğlu Data Science Institute Jul 2020 – present University of California at Berkeley, Berkeley Institute for Data Science Postdoctoral scholar and staff ethnographer Jan 2016 – June 2020 Wikimedia Foundation Research intern (full-time) May 2011 – Aug 2011 Georgetown University Research associate, Communication, Culture, and Technology (full-time) May 2009 – Aug 2010 Publications & Other Scholarly Outputs: Peer-Reviewed Journal Publications: 1. Geiger, R. S., Cope, D., Ip, J., Lotosh, M., Shah, A., Weng, J., & Tang, R. (2021). “Garbage In, Garbage Out” Revisited: What Do Machine Learning Application Papers Report About Human- Labeled Training Data?. Quantitative Science Studies, Online First. 1-32. https://doi.org/10.1162/qss_a_00144 2. Geiger, R. S., Howard, D., & Irani, L. (2021). The Labor of Maintaining and Scaling Free and Open-Source Software Projects. Proceedings of the ACM on Human-Computer Interaction, 5 (CSCW1), 1-28. https://dl.acm.org/doi/pdf/10.1145/3449249 Geiger CV 2/14 3. Scroggins, M.J., Pasquetto, I.V., Geiger, R.S., Boscoe, B.M., Darch, P.T., Cabasse-Mazel, C., Thompson, C. and Borgman, C.L. (2020). “Thorny Problems in Data (-Intensive) Science.” Communications of the ACM. -
The Internet Broke the News Industry (And Can Fix It Too)
The Internet Broke the News Industry (and Can Fix it Too) Jimmy Wales and Orit Kopel (2019) When pollsters ask Americans whether they trust the news they read, listen to, and watch, the answer is increasingly negative. This sentiment is in fact now common all over the world. Growing rates of global internet access have made countless sources of information readily available but with few checks and balances and widely varying levels of credibility. Unprecedented access to all kinds of media has not only increased competition among news providers, but it has also led to the extreme proliferation of low-quality yet plausible-looking sources of information—making it easier for political players to manipulate public opinion and to do so while denigrating established news brands. The world’s new, digital, and highly competitive media environment has created fundamental problems in the business models that journalism relies on. Print products are in terminal decline; television audiences are plummeting. Advertising around news is no longer attractive when internet giants like Google, Facebook, and Amazon offer far more effective ways to target consumers. These new financial realities have led many news organizations to adopt problematic techniques for survival: prioritizing quantity over quality and running so-called clickbait headlines. Each of these developments, combined with a lack of transparency within news organizations and the increased use of unfiltered social media platforms as news sources, contributes to a further drop in trust in the media. The decline of news organizations may seem unstoppable. But while the internet has permanently disrupted traditional media, it also presents several ways to fix it. -
Bridging the Gap: Rebuilding Citizen Trust in Media
Bridging the Gap Rebuilding Citizen Trust in Media Anya Schiffrin, Beatrice Santa-Wood, Susanna De Martino with Nicole Pope and Ellen Hume ABOUT THE AUTHORS Anya Schiffrin is the director of the Technology, Media, and Communications specialization at Columbia University’s School of International and Public Affairs, where she teaches courses on media development and innovation and social change. Among other topics, she writes on journalism and development as well as the media in Africa and the extractive sector. She served for nine years on the advisory board of the Open Society Foundations’ Program on Independent Journalism and is a member of the OSF Global board. Her most recent book is African Muckraking: 50 Years of African Investigative Journalism (Jacana: 2017). Beatrice Louise Santa-Wood recently earned her Master’s degree from the School of International and Public Affairs at Columbia University, where she specialized in human rights and was senior editor of the Journal of International Affairs. Susanna De Martino is a research assistant for Anya Schiffrin at Columbia University. She studies political science at Barnard College. Nicole Pope is a Swiss journalist and writer based in Berlin. She lived 30 years in Turkey and contributed to numerous publications, serving for 15 years as the Turkey correspondent for Le Monde. Ellen Hume is a teacher, journalist and founding member of International Media Development Advisers. She has served as White House correspondent for the Wall Street Journal, research director of the Center for Civic Media at MIT, executive director of Harvard’s Shorenstein Center on the Press, Politics and Public Policy, and as first executive director of the PBS Democracy Project. -
Blind Trust Is Not Enough”: Considering Practical Verifiability and Open Referencing in Wikipedia
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Journal of Critical Library and Information Studies Perspective “Blind Trust is Not Enough”: Considering Practical Verifiability and Open Referencing in Wikipedia Cal Murgu and Krisandra Ivings ABSTRACT This article draws attention to the often-unseen information inequalities that occur in the way that Wikipedia content is referenced. Drawing on digital information control and virtual gatekeeping scholarship, we contend that by not considering the degree to which references are practically accessible and verifiable, Wikipedia editors are implicitly promoting a control mechanism that is limiting the potential of Wikipedia to serve, as Willinsky puts it, “as a gateway to a larger world of knowledge.” We question the widespread practice of referencing peer-reviewed literature that is obscured by prohibitive paywalls. As we see it, two groups are disadvantaged by this practice. First, Wikipedia editors who lack access to the most current scholarly literature are unable to verify a reference or confirm the veracity of a fact or figure. Second, and perhaps most important, general readers are left with two unsatisfactory options in this scenario: they can either trust the authority of the citation or pay to access the article. Building on Don Fallis’ work on epistemic consequences of Wikipedia, this paper contends that promoting practically verifiable references would work to mitigate these inequalities and considers how relatively new initiatives could be used to improve the quality and utility of Wikipedia more generally. Murgu, Cal and Krisandra Ivings. “’Blind Trust is Not Enough’: Considering Practical Verifiability and Open Referencing in Wikipedia,” in “Information/Control: Control in the Age of Post-Truth,” eds.