Content Management Techniques Content Management Techniques for Fact-Checking: Models, Algorithms, and Tools – ContentCheck
Fact-checking is the task of assessing the factual accuracy of claims, typically prior to publication. Modern fact-checking is faced with a triple revolution in terms of scale, complexity, and visibility: many more claims are made and disseminated through Web and social media, they represent a complex reality and their investigation requires using multiple heterogeneous data source; finally, fact-checkig outputs themselves are interesting for the public wishing to cross-check the process. Our project brings together academic labs with expertise in data management, natural language processing, automated reasoning and data mining, and a fact-checking team of journalists from a major French Web media. We will work to establish fact-checking as a data management problem, endow it with sound foundations from the literature and/or new models as needed, design and deploy novel algorithms for automating fact-checking, and validate them by close interaction with the journalists.
Madame Ioana Manolescu (INRIA - Centre de recherche Saclay - Ile-de-France - Equipe CEDAR)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
SOCIETE EDITRICE DU MONDE
CNRS-LIMSI Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur
INSA LYON - LIRIS Institut National des Sciences Appliquées de Lyon - Laboratoire d'Informatique en Images et Systèmes d'information
INRIA Saclay - Ile-de-France/Equipe CEDAR INRIA - Centre de recherche Saclay - Ile-de-France - Equipe CEDAR
UR1-IRISA Université Rennes 1 - IRISA
Help of the ANR 711,121 euros
Beginning and duration of the scientific project: December 2015 - 48 Months