Fact checking: detection of check worthy statements through support vector machine and feed forward neural network
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Autor:innen
Autor:in (Körperschaft)
Publikationsdatum
2021
Typ der Arbeit
Studiengang
Typ
04B - Beitrag Konferenzschrift
Herausgeber:innen
Herausgeber:in (Körperschaft)
Betreuer:in
Übergeordnetes Werk
Advances in information and communication. Proceedings of the 2021 Future of Information and Communication Conference (FICC)
Themenheft
DOI der Originalpublikation
Link
Reihe / Serie
Advances in Intelligent Systems and Computing
Reihennummer
1364
Jahrgang / Band
2
Ausgabe / Nummer
Seiten / Dauer
520-535
Patentnummer
Verlag / Herausgebende Institution
Springer
Verlagsort / Veranstaltungsort
Cham
Auflage
Version
Programmiersprache
Abtretungsempfänger:in
Praxispartner:in/Auftraggeber:in
Zusammenfassung
Detection of check-worthy statements is a subtask in the fact-checking process, automation of which would decrease the time and burden required to fact-check a statement. This paper proposes an approach focused on the classification of statements into check-worthy and not check-worthy. For the current paper, a dataset is constructed by consulting different fact-checking organizations. It contains debates and speeches in the domain of politics. Thus, even the ability of check worthy approach is evaluated on this domain. It starts with extracting sentence-level and context features from the sentences, and classifying them based on these features. The feature set and context were chosen after several experiments, based on how well they differentiate check-worthy statements. The findings indicated that the context in the approach gives considerable contribution in the classification, while also using more general features to capture information from the sentences. The results were analyzed by examining all features used, assessing their contribution in classification, and how well the approach performs in speeches and debates separately to detect the check worthy statements to reduce the time and burden of fact checking process.
Schlagwörter
Fachgebiet (DDC)
330 - Wirtschaft
Veranstaltung
Future of Information and Communications Conference (FICC) 2021
Startdatum der Ausstellung
Enddatum der Ausstellung
Startdatum der Konferenz
29.04.2021
Enddatum der Konferenz
30.04.2021
Datum der letzten Prüfung
ISBN
978-3-030-73102-1
978-3-030-73103-8
978-3-030-73103-8
ISSN
Sprache
Englisch
Während FHNW Zugehörigkeit erstellt
Ja
Zukunftsfelder FHNW
Publikationsstatus
Veröffentlicht
Begutachtung
Peer-Review der ganzen Publikation
Open Access-Status
Closed
Lizenz
Zitation
AHMED, Sajjad, Klestia BALLA, Knut HINKELMANN und Flavio CORRADINI, 2021. Fact checking: detection of check worthy statements through support vector machine and feed forward neural network. In: Kohei ARAI (Hrsg.), Advances in information and communication. Proceedings of the 2021 Future of Information and Communication Conference (FICC). Cham: Springer. 2021. S. 520–535. Advances in Intelligent Systems and Computing, 1364. ISBN 978-3-030-73102-1. Verfügbar unter: https://irf.fhnw.ch/handle/11654/42805