ClaimsKG - A Knowledge Graph of Fact-Checked Claims (January, 2023)

DOI

ClaimsKG is a knowledge graph of metadata information for fact-checked claims scraped from popular fact-checking sites. In addition to providing a single dataset of claims and associated metadata, truth ratings are harmonized and additional information is provided for each claim, e.g., about mentioned entities. Please see ( https://data.gesis.org/claimskg/ ) for further details about the data model, query examples and statistics. The dataset facilitates structured queries about claims, their truth values, involved entities, authors, dates, and other kinds of metadata. ClaimsKG is generated through a (semi-)automated pipeline, which harvests claim-related data from popular fact-checking web sites, annotates them with related entities from DBpedia/Wikipedia, and lifts all data to RDF using established vocabularies (such as schema.org). The latest release of ClaimsKG covers 74066 claims and 72127 Claim Reviews. This is the fourth release of the dataset where data was scraped till Jan 31, 2023 containing claims published between 1996 and 2023 from 13 fact-checking websites. The websites are Fullfact, Politifact, TruthOrFiction, Checkyourfact, Vishvanews, AFP (French), AFP, Polygraph, EU factcheck, Factograph, Fatabyyano, Snopes and Africacheck. The claim-review (fact-checking) period for claims ranges between the year 1996 to 2023. Similar to the previous release, the Entity fishing python client ( https://github.com/hirmeos/entity-fishing-client-python ) has been used for entity linking and disambiguation in this release. Improvements have been made in the web scraping and data preprocessing pipeline to extract more entities from both claims and claims reviews. Currently, ClaimsKG contains 3408386 entities detected and referenced with DBpedia. This latest release of ClaimsKG supersedes the previous versions as it contained all the claims from the previous versions together in addition to the additional new claims as well as improved entity annotation resulting in a higher number of entities.

Total Universe / Complete enumeration

Web scraping

Identifier
DOI https://doi.org/10.7802/2620
Source https://search.gesis.org/research_data/SDN-10.7802-2620?lang=de
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=270d5f158a845c7d7f4801023678aa75bf1d9060734c3dc260bd791172be419c
Provenance
Creator Gangopadhyay, Susmita; Schellhammer, Sebastian; Boland, Katarina; Schüller, Sascha; Todorov, Konstantin; Tchechmedjiev, Andon; Zapilko, Benjamin; Fafalios, Pavlos; Jabeen, Hajira; Dietze, Stefan
Publisher GESIS Data Archive for the Social Sciences; GESIS Datenarchiv für Sozialwissenschaften
Publication Year 2023
Rights Free access (without registration) - The research data can be downloaded directly by anyone without further limitations. CC BY-SA 4.0: Attribution – ShareAlike (https://creativecommons.org/licenses/by-sa/4.0/deed.de); Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden. CC BY-SA 4.0: Attribution – ShareAlike (https://creativecommons.org/licenses/by-sa/4.0/deed.de)
OpenAccess true
Contact http://www.gesis.org/
Representation
Discipline Computer Science; Computer Science, Electrical and System Engineering; Engineering Sciences; Humanities; Linguistics; Social Sciences; Social and Behavioural Sciences