DS0707 - Interactions humain-machine, objets connectés, contenus numériques, données massives et connaissance

Content Management Techniques Content Management Techniques for Fact-Checking: Models, Algorithms, and Tools – ContentCheck

Submission summary

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.

Project coordination

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.


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

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