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Our society is struggling with an unprecedented amount of falsehood which harms wealth, democracy, and health.
Our society is struggling with an unprecedented amount of falsehood which harms wealth, democracy, and health.
Debunking misinformation and disinformation calls for interdisciplinary collaboration of and advancements in multiple areas, including journalism, communication studies, law and public policy, psychology, and political science. Computing technology plays a crucial role in it. The last few years have witnessed a substantial growth in efforts at computational fact-checking, of which many are data-driven, AI-powered, and include human in the loop. These efforts tackle various fronts, such as the detection of fabricated news, rumors, and spam on social media, automation in fact-checking, flagging clickbait articles, and discovering fake accounts and malicious social media bots.
Advancements in algorithms and AI have raised significant ethics concerns regarding fairness, transparency, trust, and misuse. The concerns are particularly pertinent to fact-checking---while fact-checkers discern truth from falsehood, who is there to check them? Furthermore, the harm of misuse of AI is already manifested in this arena. For instance, creators of falsehoods may optimize for their objectives using approaches steered by algorithms. Finally, maintaining a high bar of ethics in research itself, particularly ensuring the reproducibility of research results, is vital to the health of the enterprise.
The success of tackling misinformation lies not only in methodology and technology but also education. To help cultivate a society that is more robust to falsehoods, to break “filter bubbles” and “echo chambers”, we must raise the awareness of all aspects about misinformation and we must train a generation of Web users that are well versed in media literacy, data literacy, and logic and fallacy.
Call for Papers
Call for Papers
This workshop aims at bringing together researchers, practitioners, and educators in computer science, journalism, communication studies, information science and systems, law and public policy, psychology, and political science in order to explore four themes. Preference will be given to studies that take computational and/or data-driven approaches to the challenge.
This workshop aims at bringing together researchers, practitioners, and educators in computer science, journalism, communication studies, information science and systems, law and public policy, psychology, and political science in order to explore four themes. Preference will be given to studies that take computational and/or data-driven approaches to the challenge.
- Computational algorithms, tools, systems, and applications for tackling misinformation and disinformation.
- Study of principles, methodologies, phenomena, and policy pertinent to misinformation and disinformation, in non-computing fields, including but not limited to journalism, communication studies, information science and systems, law and public policy, psychology, and political science.
- Studies that address the ethical pitfalls in tackling misinformation and propose solutions to ensure fairness, transparency, and interpretability of tools or solutions to mitigate the challenges posed by malicious adversaries who misuse advanced computing and AI technologies.
- Misinformation-related education, including media literacy, data literacy, and logic and fallacy.
The workshop welcomes submissions on topics related to the following non-exclusive aspects, with a preference for computational and/or data-driven approaches.
The workshop welcomes submissions on topics related to the following non-exclusive aspects, with a preference for computational and/or data-driven approaches.
- Artifacts/phenomena: fact-checks, "fake news", bots, rumors, computational propaganda, spam, scams, astroturfing, fake reviews, filter bubble, echo chamber
- Computational methodology: artificial intelligence, crowdsourcing, data analytics, data and content management, data cleaning, data mining, human-computer interaction, information integration, knowledge bases and knowledge graphs, machine learning, natural language processing, search, security and privacy, social media analysis, user interface, visualization, Web technology
- Ethical pitfalls and solutions: bias, fairness, transparency, interpretability, explainability in computational fact-checking; countering misuse of algorithms in creating falsehoods; reproducibility of and resources for fact-checking research
- Education: methods, resources, practices, empirical experience and evaluation of fact-checking related education (e.g., media literacy, data literacy, and logic and fallacy)
Submission Instructions
Submission Instructions
The proceedings of the workshop will be published jointly with The Web Conference 2019 proceedings. Papers must be submitted in PDF according to the ACM format published in the ACM guidelines (www.acm.org/publications/proceedings-template), selecting the generic “sigconf” sample. The PDF files must have all non-standard fonts embedded. Workshop papers must be self-contained and in English. Papers submitted cannot exceed six pages in length, including references and appendix. Submissions are handled through EasyChair: https://easychair.org/conferences/?conf=misinfoworkshop2019
Important Dates
Important Dates
All deadlines are 11:59pm EST (Eastern Standard Time)
All deadlines are 11:59pm EST (Eastern Standard Time)
Paper submission deadline: Friday, Feb 8, 2019
Notification of acceptance: Monday, February 25, 2019
Camera-ready deadline: Sunday, March 3, 2019
Workshop date: Tuesday, May 14, 2019, San Francisco, CA - Co-located with TheWebConf 2019
Journal Special Issue
Journal Special Issue
We are discussing with journals regarding a special issue on the workshop. More details will be released here once available.
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Sponsors
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