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Behavior & Information Technology
Special Issue on Social Response to the Covid-19 Pandemic
https://think.taylorandfrancis.com/special_issues/behaviour-information-technology-covid-19/?utm_source=TFO&utm_medium=cms&utm_campaign=JPF15121
“Drinking Bleach or Cocaine will Cure Covid-19” “Ensure your
mouth and throat are always moist. Stomach acid can kill
coronavirus. It's just the flu.” “if you have a wet cough, it’s
not coronavirus - but a dry cough is” are examples of social media
fake messages related to the novel coronavirus. There is a lot of
confusing, incomplete, and just plain inaccurate information
circulating about how to prevent the COVID-19 virus. Such false or
misleading information is extremely dangerous and can lead to
death if trusted blindly. The rapid spread of information online
means that when scientists discuss as-yet unproven theories or
treatments, anxious patients can take unnecessary risks. Social
media channels are working hard to remove such misleading
information immediately. Recently Facebook, Reddit, Google,
LinkedIn, Microsoft, Twitter and YouTube have made commitment to
remove coronavirus-related disinformation and misinformation since
specific and unverified claims that incite people to take action
can result in severe damage to human health and the society.
Automating detection of such misleading information can help to
block false information immediately. False/misleading information
is one dark aspect of social media, however, there are several
other issues such as scam, racism, cyberbullying, trolling,
privacy invasion, etc.
In response, social media and tech giants are endeavoring to do
their part to mitigate these issues. Microsoft, Facebook, Google,
Reddit and LinkedIn recently have issued a joint statement
confirming they’re working together to combat fraud and
misinformation, elevate authoritative content and share critical
updates by coordinating with governments and healthcare agencies
around the world. Video platform, TikTok, has also teamed up with
the World Health Organization to publish information about the
coronavirus and hosted a live stream on how to prevent the
coronavirus from spreading and answering questions from viewers.
This special issue is in response to the ongoing COVID-19 crisis
and impacts from the social media perspective. Undoubtedly the
COVID-19 crisis and its concomitant social and economic impacts
will inspire a great number of research inquiries especially on
people’s behavior and its analysis on social media.
Papers are welcomed on the following topics but not confined to:
• Disinformation and Misinformation detection
• Fraud detection
• Social media data analytics
• Mental Health and Covid-19
• Quantitative multimedia data analysis of Covid-19
• Deep Model Design over big multi-modal social-media data
• Deep learning on cross-modal social-media
• Data mining on big cross-modal social-media networks
• Computational social-media computing and applications
• Aftershock of Covid-19 on social media
• Social-media analytics and societal behavior
• COVID-19 pandemic and even detection
• Knowledge representation in COVID-19 analysis
• Use of Covid-19 terms as figurative language
Important Dates:
• Manuscript submission deadline: Oct 15, 2020
• Review notification: Dec 1, 2020
• Revised papers due date Feb 1, 2021
• Final decision notification March 1, 2021
Special Issue Editor(s)
Guandong Xu, University of Technology Sydney, Australia,
guandong.xu@uts.edu.au
Imran Razzak, Deakin University, Australia,
imran.razzak@deakin.edu.au
Wu He, Old Domino University, USA,
WHe@odu.edu
Sheraz Ahmed, German Research Centre for Artificial Intelligence,
Germany,
Sheraz.Ahmed@dfki.de
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