[Air-L] Fwd: [SIG-IRList] CFP - Springer Social Network Analysis and Mining (SNAM) - Special Issue on Tackling COVID-19 Infodemic

[Jodi Schneider]

---------- Forwarded message ---------
From: Kai Shu <000004d7b7d15c0c-dmarc-request at listserv.acm.org>
Date: Wed, Jul 22, 2020 at 3:45 AM
Subject: [SIG-IRList] CFP - Springer Social Network Analysis and Mining
(SNAM) - Special Issue on Tackling COVID-19 Infodemic
To: <SIGIR at listserv.acm.org>


*Call For Papers*
==================
Social Network Analysis and Mining - Special Issue on Tackling COVID-19
Infodemic
Website: https://www.springer.com/journal/13278/updates/18175124


*Description*==================
While the COVID-19 pandemic continues its global devastation, numerous
accompanying challenges emerge. One important challenge is to efficiently
and effectively use recently gathered data and find computational tools to
combat the COVID-19 infodemic. An infodemic is an overabundance of
information – some accurate and some not – occurring during an epidemic.
Rampant conspiracy theories, disinformation, misinformation, and various
types of scams can spread fast by taking advantage of human gullibility,
fear, and ignorance. Therefore, there is a pressing need to manage the
infodemic to help people find trustworthy information and reliable guidance
during this global public health crisis. AI for Good holds a lot of
potential for solving societal problems including combating the infodemic,
while challenges remain. It is important to integrate theories from
different disciplines to help with the COVID-19 crisis.

In this special issue, we provide an interdisciplinary forum for
researchers and practitioners to combat the COVID-19 infodemic. We expect
novel research to study the understanding, detection, mitigation, and
measurement of the COVID-19 infodemic and potential future outbreaks. To
facilitate further research in COVID-19 infodemic, this special issue
welcomes interdisciplinary research articles, new open-access datasets,
repositories, and benchmarks, broadening research on crisis informatics and
its development.

*Topics of interest include, but are not limited to:*
====================================
- Disinformation/misinformation detection and mitigation
- Fact-checking and credibility assessment
- Computational tools to understand, measure and contain infodemic
- Diffusion and intervention of infodemic
- Bias, transparency, and fairness
- Economical impacts of infodemic
- Infodemic monitoring across countries, regions, and cultures
- Individual and societal impacts of COVID-19 infodemic
- Epidemiology, public health, and infodemic
- Psychology, marketing, and behavioral insights
- Data science, applied maths, and physics for infodemic
- Society, ethics, trust, and governance for infodemic
- Attribution and source tracing of COVID-19 infodemic
- Spatio-temporal infodemic analysis
- Social network analysis
- AI for COVID-19
- Sociological and psychological analysis of infodemic
- COVID-19 infodemic datasets, benchmarks, and repositories

*Submission Instructions*
==================
Articles reporting original and unpublished research results pertaining to
the above topics are solicited. We welcome two types of research
contributions:
(1) Research manuscripts reporting novel methodologies and results (up to
20 pages);
(2) Benchmark, Datasets, Repositories, and Demonstration Systems (up to 8
pages).

Submitted articles will follow an academic review process. Manuscripts must
be prepared according to the instruction for authors available at the
journal webpage and submitted through the publisher's online submission
system, available at https://www.editorialmanager.com/snam/default.aspx.
Please note: when submitting, please choose the correct special issue, i.e.
"*SI: Tackling COVID-19 Infodemic*".

*Important Dates*
==================
Submission deadline: *October 15, 2020*
Notification: November 25, 2020
Camera-ready deadline: December 30, 2020

*Guest Editors *
==================
Kai Shu, Illinois Institute of Technology, kshu at iit.edu
Miriam Metzger, University of California, Santa Barbara, metzger at ucsb.edu
Huan Liu, Arizona State University, huanliu at asu.edu

All questions can be directed to Kai Shu at kshu at iit.edu.