Wiki Workshop 2019

A forum bringing together researchers exploring all aspects of Wikipedia, Wikidata, and other Wikimedia projects. Held at The Web Conference 2019 in San Francisco, Calif., May 14, 2019.

  • Feb. 6, 2019: Denny Vrandečić confirmed as invited speaker.
  • Feb. 6, 2019: Erica Kochi confirmed as invited speaker.
  • Jan. 23, 2019: Jure Leskovec confirmed as invited speaker.
  • Jan. 23, 2019: Neil Thompson confirmed as invited speaker.
  • Jan. 23, 2019: Timnit Gebru confirmed as invited speaker.
  • Jan. 20, 2019: Workshop date announced: Tuesday, May 14, 2019.
  • Dec. 6, 2018: Wiki Workshop 2019 webpage online.

We will have a series of invited talks by academia and industry experts, as well as a combination of lightning talks and a poster session for the accepted papers.

Details to be determined.

More speakers to be announced soon—stay tuned!

Denny Vrandečić (Google)

Title and abstract TBA

Denny works at the Google Knowledge Graph. He previously has worked at the Karlsruhe Institute of Technology (2004-2012), the University of Southern California (2010), and as the project director of Wikidata at Wikimedia Deutschland (2012/13). His research interests are massive collaborative systems, knowledge bases, and the Semantic Web.

Erica Kochi (UNICEF)

Title and abstract TBA

Erica co-founded and co-leads UNICEF’s Innovation Unit, a group tasked with identifying, prototyping and scaling technologies and practices that improve UNICEF’s work on the ground. Erica also serves as Innovation Advisor to UNICEF’s Executive Director. Erica co-taught ‘Design for UNICEF’ at NYU’s ITP and has lectured at the Yale School of Management, Harvard University, The Art Center, Stanford University School of Engineering, and Columbia School of International and Public Affairs on technology, innovation, design, and international development.

Jure Leskovec (Stanford University)

Title and abstract TBA

Jure is an associate professor of Computer Science at Stanford University. His research focuses on mining and modeling large social and information networks, their evolution, and diffusion of information and influence over them. Problems he investigates are motivated by large scale data, the Web and online media.

Timnit Gebru (Google)

Title and abstract TBA

Timnit is a research scientist in the Ethical AI team at Google. Prior to that, she was a postdoc at Microsoft Research, New York, and a PhD student in the Stanford Artificial Intelligence Laboratory. She is currently studying the ethical considerations underlying any data mining project, and methods of auditing and mitigating bias in sociotechnical systems. The New York Times, MIT Tech Review and others have recently covered her work. As a cofounder of the group Black in AI, she works to both increase diversity in the field and reduce the negative impacts of racial bias in training data used for human- centric machine learning models.

Neil Thompson (MIT)

Title and abstract TBA

Neil is a Research Scientist at MIT’s Computer Science and Artificial Intelligence Lab and a Visiting Professor at the Lab for Innovation Science at Harvard. He is also an Associate Member of the Broad Institute, and was previously an Assistant Professor of Innovation and Strategy at the MIT Sloan School of Management, where he co-directed the Experimental Innovation Lab (X-Lab). Neil did his PhD in Business and Public Policy at Berkeley. Prior to academia, he worked at organizations such as Lawrence Livermore National Laboratories, Bain and Company, the United Nations, the World Bank, and the Canadian Parliament.

Workshop date: Tuesday, May 14, 2019

If authors want paper to appear in proceedings:

  • Submission deadline: January 31, 2019
  • Author feedback: February 21, 2019
  • Camera-ready version due: March 3, 2019

If authors do not want paper to appear in proceedings:

  • Submission deadline: March 14, 2019
  • Author feedback: March 28, 2019
Note: If you need a visa to travel to U.S. and your application for the visa depends on your workshop paper being accepted, we would advise you to submit your workshop paper for the January 31 deadline.

Wikipedia is one of the most popular sites on the Web, a main source of knowledge for a large fraction of Internet users, and one of the very few projects that make not only their content but also many activity logs available to the public. Furthermore, other Wikimedia projects, such as Wikidata and Wikimedia Commons, have been created to share other types of knowledge with the world for free. For a variety of reasons (quality and quantity of content, reach in many languages, process of content production, availability of data, etc.) such projects have become important objects of study for researchers across many subfields of the computational and social sciences, such as social network analysis, artificial intelligence, linguistics, natural language processing, social psychology, education, anthropology, political science, human–computer interaction, and cognitive science.

The goal of this workshop is to bring together researchers exploring all aspects of Wikimedia projects such as Wikipedia, Wikidata, and Commons. With members of the Wikimedia Foundation's Research team on the organizing committee and with the experience of successful workshops in 2015, 2016, 2017, and 2018, we aim to continue facilitating a direct pathway for exchanging ideas between the organization that coordinates Wikimedia projects and the researchers interested in studying them.

Topics of interest include, but are not limited to

  • new technologies and initiatives to grow content, quality, diversity, and participation across Wikimedia projects
  • use of bots, algorithms, and crowdsourcing strategies to curate, source, or verify content and structured data
  • bias in content and gaps of knowledge
  • diversity of Wikimedia editors and users
  • detection of low-quality, promotional, or fake content, as well as fake accounts (e.g., sock puppets)
  • questions related to community health (e.g., sentiment analysis, harassment detection)
  • understanding editor motivations, engagement models, and incentives
  • Wikimedia consumer motivations and their needs: readers, researchers, tool/API developers
  • innovative uses of Wikipedia and other Wikimedia projects for AI and NLP applications
  • consensus-finding and conflict resolution on editorial issues
  • participation in discussions and their dynamics
  • dynamics of content reuse across projects and the impact of policies and community norms on reuse
  • privacy
  • collaborative content creation (unstructured, semi-structured, or structured)
  • innovative uses of Wikimedia projects' content and consumption patterns as sensors for real-world events, culture, etc.
  • open-source research code, datasets, and tools to support research on Wikimedia contents and communities

Papers should be 1 to 8 pages long and will be published on the workshop webpage and optionally (depending on the authors' choice) in the workshop proceedings. The review process will be single-blind (as opposed to double-blind), i.e., authors should include their names and affiliations in their submissions. Authors whose papers are accepted to the workshop will have the opportunity to participate in a poster session.

We explicitly encourage the submission of preliminary work in the form of extended abstracts (1 or 2 pages).

Papers should be 1 to 8 pages long. We explicitly encourage the submission of preliminary work in the form of extended abstracts (1 or 2 pages). No need to anonymize your submissions.

For submission dates, see above.

  • Michele Catasta, Stanford University
  • Lucas Dixon, Jigsaw
  • Besnik Fetahu, L3S Hannover
  • Andrea Forte, Drexel University
  • Gary Hsieh, University of Washington
  • Yiqing Hua, Cornell University
  • Isaac Johnson, Wikimedia Foundation
  • Os Keyes, University of Washington
  • Markus Kroetzsch, University of Dresden
  • Florian Lemmerich, RWTH Aachen University
  • Lauren Maggio, Uniformed Services University
  • David McDonald, University of Washington
  • Jonathan Morgan, Wikimedia Foundation
  • André Panisson, ISI Foundation
  • Daniela Paolotti, ISI Foundation
  • Tiziano Piccardi, EPFL
  • Dario Rossi, Huawei
  • Diego Saez-Trumper, Wikimedia Foundation
  • Markus Strohmaier, RWTH Aachen University
  • Nithum Thain, Jigsaw
  • Michele Tizzoni, ISI Foundation
  • Morten Warncke-Wang, Wikimedia Foundation
  • Joe Wass, Crossref
  • Ramtin Yazdanian, EPFL
  • Amy Zhang, MIT

Robert West

Bob is an assistant professor of Computer Science at EPFL, where he heads the Data Science Lab. His research aims to understand, predict, and enhance human behavior in social and information networks by developing techniques in data science, data mining, network analysis, machine learning, and natural language processing. He holds a PhD in computer science from Stanford University.

Miriam Redi

Miriam is a Research Scientist at the Wikimedia Foundation and Visiting Research Fellow at King's College London. Formerly, she worked as a Research Scientist at Yahoo! Labs in Barcelona and Nokia Bell Labs in Cambridge. She received her PhD from EURECOM, Sophia Antipolis. She conducts research in social multimedia computing, working on fair, interpretable, multimodal machine learning solutions to improve knowledge equity.

Dario Taraborelli

Dario is a social computing researcher and the Wikimedia Foundation's Head of Research. His current interests focus on online collaboration, open science, and the measurement and discoverability of scientific knowledge. He holds a PhD in cognitive science from the École des Hautes Études en Sciences Sociales.

Please direct your questions to wikiworkshopgooglegroupscom.