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 good.
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 pandemics.
************ 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: https://aitdmp.conceptechint.net Submission Link: https://goodit2021.hotcrp.com/
************ 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: https://www.acm.org/publications/proceedings-template 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 at: www.overleaf.com/gallery/tagged/acm-official
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 http://www.sigcas.org/