Ethical and eXplainable Natural Language Processing and Graph Neural Networks for the detection of fake news and the prevention of disinformation campaigns

The main objective of EthicalNews is to investigate a new Ethical and eXplainable Natural Language Processing framework aimed at detecting fake news and preventing misinformation, for final validation in a simulated laboratory environment. The research conducted in this project will include the study of the ethical, legal, and sociological framework for fake news detection, research into eXplainable Graph Neural Symbolic Learning for detecting fake profiles, as well as the research and design of cognitive computing algorithms and eXplainable Deep Reinforcement Learning for the prevention and mitigation of misinformation campaigns. 

Oriented to the Challenges of Society, within the framework of the State Plan for Scientific and Technical Research and Innovation 2017-2020, aimed at granting aid to R&D&I projects in strategic lines, in public-private collaboration. 

Funding body:
This project is funded by the Ministry of Science and Innovation, within the State I+D+i Program.
Reference:
PLEC2021-008132
Funding:
Project Budget: 591.751,64€.
AIR INSTITUTE Budget: 299.446,25€.

Funding organization

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