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CoulterOzler at CheckThat! 2022: Detecting fake news with transformers
Publisher
CEUR-WSCitation
Ozler, K. B., & Coulter, R. (2022). CoulterOzler at CheckThat! 2022: Detecting fake news with transformers. In 2022 Conference and Labs of the Evaluation Forum, CLEF 2022 (pp. 606-615).Journal
CEUR Workshop ProceedingsRights
Copyright © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
In the age of the internet, people interact with each other more often than ever. Almost everybody with internet access has an affiliation with a social media website. With this popularity, spreading of misinformation has inevitably become a huge problem of the current age. In recent years, 2016 US Presidential Election brought the attention to fake news. With the Coronavirus Pandemic misinformation became an increasingly popular area to research in academia. To be a part of the research on detecting misinformation in the internet, we participated in task 3: Fake News Detection of the Checkthat! Lab at CLEF2022. In this paper, we show the details of our system consisting of data collection, transformer based pre-trained models and extensive preprocessing methods. We achieved an F1-score (macro) of 0.328 against a top score of 0.339 on the official test set. © 2022 Copyright for this paper by its authors.Note
Open access journalISSN
1613-0073Version
Final published versionCollections
Except where otherwise noted, this item's license is described as Copyright © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).