Special Issue Information Special Issue Call for Paper Other Special Issues on this journal Closed Special Issues
Tackling COVID-19 Infodemic

Tackling COVID-19 Infodemic

Journal
Impact Score 2.97

OFFICIAL WEBSITE

Special Issue Information

Submission Deadline: 15-10-2020
Journal Impact Score: 2.97
Journal Name: Social Network Analysis and Mining
Publisher: Social Network Analysis and Mining
Journal & Submission Website: https://www.springer.com/journal/13278

Special Issue Call for Papers

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 behavioural 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/snamPlease 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, ​[email protected]

Miriam Metzger, University of California, Santa Barbara, ​[email protected]  

Huan Liu, Arizona State University, ​[email protected] 

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Closed Special Issues

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Tackling COVID-19 Infodemic

Tackling COVID-19 Infodemic

Social Network Analysis and Mining
Closing date: 15-10-2020 G2R Score: 2.97