ClaimsKG - A Knowledge Graph of Fact-Checked Claims (August, 2022)

DOI

ClaimsKG is a knowledge graph of metadata information for 59580 fact-checked claims scraped from 13 fact-checking sites. In addition to providing a single dataset of claims and associated metadata, truth ratings are harmonised 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 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 59580 claims. The data was scraped till August, of 2022 containing claims published between the years 1996-2022 from 13 factchecking websites. The claim-review (fact checking) period for claims ranges between the year 1996 to 2022. Entity fishing python client (https://github.com/hirmeos/entity-fishing-client-python) has been used for entity linking and disambiguation in this release. The dataset contains a total of 1371271 entities detected and referenced with DBpedia. More information, such as detailed statistics, query examples and a user-friendly interface to explore the knowledge graph is available at: https://data.gesis.org/claimskg/ . The first two releases of ClaimsKG are hosted at Zenodo (https://doi.org/10.5281/zenodo.3518960), ClaimsKGV1.0 (published on 04.04.2019), ClaimsKGV2.0 (published on 01.09.2019). This latest release of ClaimsKG supersedes the previous versions as it contains all the claims from the previous versions together with additional claims as well as improved entity annotations.

Total Universe / Complete enumeration

Web scraping

Identifier
DOI https://doi.org/10.7802/2469
Source https://search.gesis.org/research_data/SDN-10.7802-2469?lang=de
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=8662fbeb8de20ed35654de4a4f75d3ff527b895690a783aad002e84384dfd317
Provenance
Creator Gangopadhyay, Susmita; 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 2022
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