1st Workshop on Automatic Detection of Fake News in Social Media (ADFNSM 2021)

Scope:

The current torrent of information conveyed by social networks has escalated the impact of the so called “fake news", a term used to describe erroneous information, many times desinformation, and sometimes gossips or rumors. Recently, “fake news” have been reported as a means to promote and demote presidential candidates in elections, to escalate fear and terror and also to create false expectations for the cure of diseases. This type of information mines the credibility of social media, eventually damages the reputation of people without real base for that, and ultimately poses a danger situation to the democracy. In this workshop we intend to address these concerns, describe them in scientific ways such that their identification and mitigation is simpler, implementable and, hopefully, fully automatic. We invite authors to submit works based on the following topics.

Topics of interest:

•    Data mining for Fake News identification
•    Identification of rumors, gossips, click bait or biased information in Social Networks
•    Models for spreading and propagation of Fake News
•    New metrics for Fake News impact and accountability
•    Reputation of Social Media Accounts
•    Browser Plug-Ins for Fake News identification and warnings
•    Automatic distinction of intended and un-intended erroneous content
•    Visualization of methods for Fake News in social media
•    NLP for Fake News detection
•    Fake and Deep Fake image identification
•    Deep Learning for Fake News detection
•    Creation of synthetic Fake News for data balance


Organizing Committee:

•    Álvaro Figueira Faculty of Sciences / Department of Computer Science University of Porto, Porto, Portugal, This email address is being protected from spambots. You need JavaScript enabled to view it.
•    Julio Amador Lopez, Data Science Institute / William Penney Laboratory Imperial College London South Kensington London, United Kingdom, This email address is being protected from spambots. You need JavaScript enabled to view it.


Program Committee:

•    Ana Azevedo, CEOS.PP / ISCAP / P.PORTO
•    Ana Alves,Centre for Informatics and Systems - University of Coimbra
•    Juan Gómez Romero, Department of Computer Science and Artificial Intelligence - University of Granada.
•    Luís Torgo, Faculty of Computer Science, Dalhousie University
•    Miguel Molina-Solana, University of Granada
•    Nuno Guimaraes, CRACS / INESCTEC
•    Nuno Moniz, INESC TEC and University of Porto
•    Ricardo Campos, Ci2 - Polytechnic Institute of Tomar; INESC TEC
•    Rita P. Ribeiro, LIAAD - University of Porto
•    Vimala Balakrishnan, University of Malaya - Faculty of Computer Science & Information Technology

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