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** Apologies for cross-posting **Workshop website:
http://claws.cc.gatech.edu/mis2-kdd2021Call for papers
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
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Measuring real world and online impact
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Deception in misinformation and misbehavior
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Reputation manipulation
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Measuring economic, ideological, and other rationale behind
creation
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Rationale behind spread and success
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Targets or victims of misbehavior and misinformation
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Effect of echo chambers, personalization, confirmation bias, and
other
socio-psychological and technological phenomenon
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Detection methods using graphs, text, behavior, image, video, and
audio
analysis
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Adversarial analysis of misbehavior and misinformation
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Prevention and mitigation techniques, tools, and countermeasures
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Theoretical and/or empirical modeling of spread
-
Visualizing spread
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Anonymity, security, and privacy aspects of data collection
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Usable security in misbehavior detection
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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
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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.
Format
Papers must be submitted in PDF according to the new ACM format
published
in ACM guidelines
<http://www.acm.org/publications/proceedings-template>,
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:
https://cmt3.research.microsoft.com/KDDMIS2021
Important Dates
-
Workshop Paper Submission: June 1st, 2021
-
Workshop Paper Notification: June 10th, 2021
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Camera ready deadline: July 1st, 2021
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Workshop date: August 14-18, 2021
Organizers
Srijan Kumar
<https://www.cc.gatech.edu/~srijan/>, Georgia
Institute of
Technology
Aude Hofleitner
<https://research.fb.com/people/hofleitner-aude/>, Facebook
Meng Jiang
<http://www.meng-jiang.com/>, University of Notre
Dame
Neil Shah
<http://nshah.net/>, Snap
Kai Shu
<http://www.cs.iit.edu/~kshu/>, Illinois Institute
of Technology
Contact
Please direct all questions to
kdd_mis2@googlegroups.com
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