@inproceedings{eldifrawi-etal-2024-automated,
title = "Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approaches",
author = "Eldifrawi, Islam and
Wang, Shengrui and
Trabelsi, Amine",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.luhme-long.361/",
doi = "10.18653/v1/2024.acl-long.361",
pages = "6679--6692",
abstract = "Automated Fact-Checking (AFC) is the automated verification of claim accuracy. AFC is crucial in discerning truth from misinformation, especially given the huge amounts of content are generated online daily. Current research focuses on predicting claim veracity through metadata analysis and language scrutiny, with an emphasis on justifying verdicts. This paper surveys recent methodologies, proposinga comprehensive taxonomy and presenting the evolution of research in that landscape. A comparative analysis of methodologies and futuredirections for improving fact-checking explainability are also discussed."
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="eldifrawi-etal-2024-automated">
<titleInfo>
<title>Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approaches</title>
</titleInfo>
<name type="personal">
<namePart type="given">Islam</namePart>
<namePart type="family">Eldifrawi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Shengrui</namePart>
<namePart type="family">Wang</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Amine</namePart>
<namePart type="family">Trabelsi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-08</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Lun-Wei</namePart>
<namePart type="family">Ku</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Andre</namePart>
<namePart type="family">Martins</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vivek</namePart>
<namePart type="family">Srikumar</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Bangkok, Thailand</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Automated Fact-Checking (AFC) is the automated verification of claim accuracy. AFC is crucial in discerning truth from misinformation, especially given the huge amounts of content are generated online daily. Current research focuses on predicting claim veracity through metadata analysis and language scrutiny, with an emphasis on justifying verdicts. This paper surveys recent methodologies, proposinga comprehensive taxonomy and presenting the evolution of research in that landscape. A comparative analysis of methodologies and futuredirections for improving fact-checking explainability are also discussed.</abstract>
<identifier type="citekey">eldifrawi-etal-2024-automated</identifier>
<identifier type="doi">10.18653/v1/2024.acl-long.361</identifier>
<location>
<url>https://aclanthology.org/2024.luhme-long.361/</url>
</location>
<part>
<date>2024-08</date>
<extent unit="page">
<start>6679</start>
<end>6692</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approaches
%A Eldifrawi, Islam
%A Wang, Shengrui
%A Trabelsi, Amine
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F eldifrawi-etal-2024-automated
%X Automated Fact-Checking (AFC) is the automated verification of claim accuracy. AFC is crucial in discerning truth from misinformation, especially given the huge amounts of content are generated online daily. Current research focuses on predicting claim veracity through metadata analysis and language scrutiny, with an emphasis on justifying verdicts. This paper surveys recent methodologies, proposinga comprehensive taxonomy and presenting the evolution of research in that landscape. A comparative analysis of methodologies and futuredirections for improving fact-checking explainability are also discussed.
%R 10.18653/v1/2024.acl-long.361
%U https://aclanthology.org/2024.luhme-long.361/
%U https://doi.org/10.18653/v1/2024.acl-long.361
%P 6679-6692
Markdown (Informal)
[Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approaches](https://aclanthology.org/2024.luhme-long.361/) (Eldifrawi et al., ACL 2024)
ACL