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MIS2-KDD 2021 : The Second International MIS2 Workshop: Misinformation and Misbehavior Mining on the Web


When Apr 18, 2021 - Aug 19, 2021
Where Virtual
Submission Deadline Jun 1, 2021
Notification Due Jun 10, 2021
Final Version Due Jul 1, 2021
Categories    data mining   misinformation   misbehavior

Call For Papers

The Second International MIS2 Workshop: Misinformation and Misbehavior Mining on the Web


The web is a space for all, allowing participating individuals to read, publish and share content openly. Despite its groundbreaking benefits in areas such as education and communication, it has also become a breeding ground for misbehavior and misinformation: any individual can reach thousands of people on the web near-instantaneously, purporting whatever they wish while also being shielded by anonymity. This capacity has led to rampant increases in misbehavior and misinformation vectors, via harassment, online scams, spread of propaganda, hate speech, deceptive reviews and more. Such issues have severe implications on both social and financial fronts.

The study of misinformation and misbehavior mining has become focal for researchers across many subfields of data, computational and social sciences, including network science, machine learning, cybersecurity, privacy, natural language processing, human computer interaction and more. MIS2 @ KDD 2021 provides a venue for researchers working in, or adjacent to these diverse areas to coalesce around central and timely topics in online misinformation and misbehavior, and present recent advances in research.

Topics of interest include (but are not limited to):
- Empirical characterization of false information
- Measuring real world and online impact
- Deception in misinformation and misbehavior
- Reputation manipulation
- Measuring economic, ideological, and other rationale behind creation
- Rationale behind spread and success
- Targets or victims of misbehavior and misinformation
- Effect of echo chambers, personalization, confirmation bias, and other socio-psychological and technological phenomenon
- Detection methods using graphs, text, behavior, image, video, and audio analysis
- Adversarial analysis of misbehavior and misinformation
- Prevention and mitigation techniques, tools, and countermeasures
- Theoretical and/or empirical modeling of spread
- Visualizing spread
- Anonymity, security, and privacy aspects of data collection
- Usable security in misbehavior detection
- Ethics, privacy, transparency, fairness, and biases in current tools and techniques
- Case studies

Paper Submission
We encourage submissions with both academic and industrial motivations, of the following types:
- Novel research papers in full or short length
- Demo papers
- Survey papers
- Comparison papers of existing methods and tools
- Work-in-progress papers
- Case studies
- Extended abstracts
- Relevant work that has been recently published (must select to opt out from publication in companion proceedings of the workshop)
- Work that will be presented at the main conference of KDD 2021 (the submission should mention that your paper has been accepted at the conference)

We explicitly encourage the submission of preliminary work in the form of extended abstracts (2 pages).
All submissions will be peer-reviewed by at least 2 reviewers, and all accepted manuscripts will be presented (virtually) at the workshop. Additionally, accepted papers will be published in the companion proceedings of the KDD conference and ACM digital library, unless the authors choose to opt out from publication.

Papers must be submitted in PDF according to the new ACM format published in ACM guidelines, selecting the generic "sigconf" sample, with a font size no smaller than 9pt. Submissions should be 2 to 8 pages long. No need to anonymize your submission.

Submission Link
Papers should be submitted via the CMT:

Important Dates (Subject to Change)
Workshop Paper Submission: June 1st, 2021
Workshop Paper Notification: June 10th, 2021
Camera ready deadline: July 1st, 2021
Workshop date: August 14-18, 2021

Please direct all questions to

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