-------- Forwarded Message -------- Subject: [AISWorld] CFP: Social Response to the Covid-19 Pandemic Date: Sat, 6 Jun 2020 15:18:13 +0000 From: He, Wu WHe@odu.edu To: aisworld@lists.aisnet.org aisworld@lists.aisnet.org

Behavior & Information Technology Special Issue on Social Response to the Covid-19 Pandemic ​ https://think.taylorandfrancis.com/special_issues/behaviour-information-tech... ​ ​“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 _______________________________________________ AISWorld mailing list AISWorld@lists.aisnet.org