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Andrew Zayine <[log in to unmask]>
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Andrew Zayine <[log in to unmask]>
Mon, 29 Mar 2021 09:44:21 +0100
text/plain (108 lines)
Call For Papers: Special Track on AI for Tackling Dis/Misinformation
during Pandemics In conjunction with the ACM International Conference
on Information Technology for Social Good (GoodIT 2021)

The GoodIT conference is sponsored by ACM SIGCAS, the Association for
Computing Machinery's Special Interest Group on Computers & Society.
The conference focuses on the application of IT technologies to social

The Special Track on AI for Tackling Dis/Misinformation during
Pandemics focuses on new data technologies based on artificial
intelligence, data governance, machine learning, natural language
processing, and social network analysis to aid experts in analyzing
large volumes of social media data in order to detect fake news,
misinformation, and disinformation. A number of open challenges need
more investigation from the research community, such as recent trends
in composing information disorder by combining false and real content,
the mechanisms that drive fake content diffusion during pandemics, how
to differentiate fake content from personal viewpoints, why people
tend to believe fake content and make decisions based on it during
pandemics, and what are the different motivations behind the
dissemination of fake content.  Fact-checking and claim verification
are two important strategies that are worth incorporating in the
automated tackling and curtailment of fake content during and after

************ Key Dates ************
Papers Submission Due:      May 1, 2021
Authors Notifications:         June 22, 2021
Final Manuscript Due:         July 10, 2021
GoodIT 2021:                    September 09-11, 2021

************ Important Links ************
Special Track Website:
Submission Link:

************ Submission Guidelines  ************
All submissions will be reviewed using a single-blind review process.
The identity of referees will not be revealed to authors, but authors
can keep their names on the submitted papers, on figures,
bibliography, etc.

Papers should not exceed 6 pages (US letter size) double column
including figures, tables, and references in standard ACM format.
Papers must be submitted electronically in printable PDF form.
Templates for the standard ACM format can be found here: No changes to
margins, spacing, or font sizes are allowed from those specified by
the style files. Papers violating the formatting guidelines will be
returned without review.

ACM has partnered with Overleaf, a free cloud-based, collaborative
authoring tool, to provide an ACM LaTeX authoring template. The ACM
LaTeX template on Overleaf platform is available to all ACM authors

Accepted papers will be included in the ACM Digital Library. Special
issues associated with the conference are being organized.

************ Topics ************
Papers on practical as well as on theoretical topics and problems in
various topics related to rumors, fake news, misinformation, and
disinformation during and after pandemics, are invited, with special
emphasis on novel techniques and tools for automated tackling and
curtailment of fake content during and after pandemics. Topics include
(but are not limited to):
-AI approaches for the detection of online influence and manipulation
-AI approaches to identify misinformation and disinformation campaigns
-AI approaches for spotting misinformation and disinformation spreaders.
-Social media mining for automated detection of misinformation
propagation and disinformation circulation
-AI approaches for automated identification and verification of claims
-AI approaches for intention detection for misinformation and
disinformation contents
-AI approaches for credibility assessment of Social media sources
-AI approaches for fake news curtailment, filtering and prevention.
-AI approaches for analysis/detection of distributed and
multi-platform misinformation and disinformation disseminations
-AI approaches for predicting the Impact of misinformation and
disinformation during pandemics
-New datasets and evaluation methodologies to aid in automated
detection and analysis of misinformation and disinformation content in
social media channels

**********The Conference Sponsored by**********
Association for Computing Machinery's Special Interest Group on
Computers & Society



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