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A linked data model for facts, statements and beliefs

  • IRISA

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationThe Web Conference 2019 - Companion of the World Wide Web Conference, WWW 2019
PublisherAssociation for Computing Machinery, Inc
Pages988-993
Number of pages6
ISBN (Electronic)9781450366755
DOIs
Publication statusPublished - 13 May 2019
Event2019 World Wide Web Conference, WWW 2019 - San Francisco, United States
Duration: 13 May 201917 May 2019

Publication series

NameThe Web Conference 2019 - Companion of the World Wide Web Conference, WWW 2019

Conference

Conference2019 World Wide Web Conference, WWW 2019
Country/TerritoryUnited States
CitySan Francisco
Period13/05/1917/05/19

Keywords

  • Data journalism
  • Fact-checking
  • Linked data
  • Tweet analysis

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