Co-inform (H2020)

Misinformation generates misperceptions, which have affected policies in many domains, including economy, health, environment, and foreign policy. Co-Inform empowers citizens, journalists, and policymakers with co-created socio-technical solutions to increase resilience to misinformation, and generates more informed behaviors and policies. The aim of Co-Inform is to co-create these solutions, with citizens, journalists, and policymakers, for (a) detecting and combating a variety of misinforming posts and articles on social media, (b) supporting, persuading, and healthy misinformation-resilient behavior, (c) bridging between the public on social media, external fact-checking journalists, and policymakers, (d) understanding and predicting which misinforming news and content are likely to spread across which parts of the network and demographic sectors, (e) infiltrating echo-chambers on social media, to expose confirmation-biased networks to different perceptions and corrective information, and (f) providing policymakers with advanced misinformation analysis to support their policy-making process and validation.

To achieve these goals, Co-Inform will bring together a multidisciplinary team of scientists and practitioners, to foster co-creational methodologies and practices for engaging stakeholders in combating misinformation posts and news articles, combined with advanced intelligent methods for misinformation detection, misinformation flow prediction, and real-time processing and measurement of crowds’ acceptance or refusal of misinformation. Co-Inform tools and platforms will be made freely available and open-sourced to maximize benefit and reuse. Three main stakeholder groups will be directly engaged throughout this process; citizens, journalists, and policymakers.

eParticipation
Data Mining
Machine Learning
Disinformation - Fake News
eCommerce
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Team Members

Related to Current Project

Faculty Member
Main Research Interests: Business Information Systems, eGovernment, Digital Transformation, Public Sector Innovation, eParticipation, Interoperability, Open Data, Linked Data, Semantic Web, eCommerce
Team Role: Director
Research Associate
Main Research Interests: eGovernment, Open Data, Linked Data, Semantic Web, Business Semantic Standards, Metadata, Data Analysis, e-Learning
Team Role: Manager
Faculty Member, Research Associate
Main Research Interests: Data Analysis, Data Mining, Deep Learning, Machine Learning, Natural Language Processing, Disinformation - Fake News
Team Role: Coordinator
Research Associate
Main Research Interests: eGovernment, Public Sector Innovation, Machine Learning
Team Role: Researcher
Research Associate
Main Research Interests: eGovernment, Data Analysis, Machine Learning, Natural Language Processing, Disinformation - Fake News, Digital Marketing
Team Role: Coordinator, Researcher
PhD Candidate
Main Research Interests: Deep Learning, Machine Learning, Natural Language Processing, Knowledge Graphs
Team Role: Researcher