A Linked Data Model for Facts, Statements and Beliefs

Ludivine Duroyon (1) , François Goasdoué (1) , Ioana Manolescu (2)

1 SHAMAN - Symbolic and Human-centric view of dAta MANagement
2 CEDAR - Rich Data Analytics at Cloud Scale

A frequent journalistic fact-checking scenario is concerned with the analysis of statements made by individuals, whether in public or in private contexts, and the propagation of information and hearsay ("who said/knew what when"). Inspired by our collaboration with fact-checking journalists from Le Monde, France's leading newspaper , we describe here a Linked Data (RDF) model, endowed with formal foundations and semantics, for describing facts, statements, and beliefs. Our model combines temporal and belief dimensions to trace propagation of knowledge between agents along time, and can answer a large variety of interesting questions through RDF query evaluation. A preliminary feasibility study of our model incarnated in a corpus of tweets demonstrates its practical interest.

Mots clés: Data journalism; linked data; fact-checking; tweet analysis

Domaines: Base de données [cs.DB]; Web; Intelligence artificielle [cs.AI]

Ludivine Duroyon, François Goasdoué, Ioana Manolescu. A Linked Data Model for Facts, Statements and Beliefs. The Web Conference 2019 - International Workshop on Misinformation, Computational Fact-Checking and Credible Web, May 2019, San Francisco, United States. ⟨10.1145/3308560.3316737⟩. ⟨hal-02057980⟩