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    <titleInfo>
        <title>Veritas Annotator: Discovering the Origin of a Rumour</title>
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    <name type="personal">
        <namePart type="given">Lucas</namePart>
        <namePart type="family">Azevedo</namePart>
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    <name type="personal">
        <namePart type="given">Mohamed</namePart>
        <namePart type="family">Moustafa</namePart>
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            <title>Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER)</title>
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        <name type="personal">
            <namePart type="given">James</namePart>
            <namePart type="family">Thorne</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Andreas</namePart>
            <namePart type="family">Vlachos</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Oana</namePart>
            <namePart type="family">Cocarascu</namePart>
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        <name type="personal">
            <namePart type="given">Christos</namePart>
            <namePart type="family">Christodoulopoulos</namePart>
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        <name type="personal">
            <namePart type="given">Arpit</namePart>
            <namePart type="family">Mittal</namePart>
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            <publisher>Association for Computational Linguistics</publisher>
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    <abstract>Defined as the intentional or unintentionalspread of false information (K et al., 2019)through context and/or content manipulation,fake news has become one of the most seriousproblems associated with online information(Waldrop, 2017). Consequently, it comes asno surprise that Fake News Detection hasbecome one of the major foci of variousfields of machine learning and while machinelearning models have allowed individualsand companies to automate decision-basedprocesses that were once thought to be onlydoable by humans, it is no secret that thereal-life applications of such models are notviable without the existence of an adequatetraining dataset. In this paper we describethe Veritas Annotator, a web application formanually identifying the origin of a rumour. These rumours, often referred as claims,were previously checked for validity byFact-Checking Agencies.</abstract>
    <identifier type="citekey">azevedo-moustafa-2019-veritas</identifier>
    <identifier type="doi">10.18653/v1/D19-6614</identifier>
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        <url>https://aclanthology.org/D19-6614</url>
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        <date>2019-11</date>
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            <start>90</start>
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%0 Conference Proceedings
%T Veritas Annotator: Discovering the Origin of a Rumour
%A Azevedo, Lucas
%A Moustafa, Mohamed
%Y Thorne, James
%Y Vlachos, Andreas
%Y Cocarascu, Oana
%Y Christodoulopoulos, Christos
%Y Mittal, Arpit
%S Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F azevedo-moustafa-2019-veritas
%X Defined as the intentional or unintentionalspread of false information (K et al., 2019)through context and/or content manipulation,fake news has become one of the most seriousproblems associated with online information(Waldrop, 2017). Consequently, it comes asno surprise that Fake News Detection hasbecome one of the major foci of variousfields of machine learning and while machinelearning models have allowed individualsand companies to automate decision-basedprocesses that were once thought to be onlydoable by humans, it is no secret that thereal-life applications of such models are notviable without the existence of an adequatetraining dataset. In this paper we describethe Veritas Annotator, a web application formanually identifying the origin of a rumour. These rumours, often referred as claims,were previously checked for validity byFact-Checking Agencies.
%R 10.18653/v1/D19-6614
%U https://aclanthology.org/D19-6614
%U https://doi.org/10.18653/v1/D19-6614
%P 90-98

Markdown (Informal)

[Veritas Annotator: Discovering the Origin of a Rumour](https://aclanthology.org/D19-6614) (Azevedo & Moustafa, 2019)

• Veritas Annotator: Discovering the Origin of a Rumour (Azevedo & Moustafa, 2019)

ACL

• Lucas Azevedo and Mohamed Moustafa. 2019. Veritas Annotator: Discovering the Origin of a Rumour. In Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER), pages 90–98, Hong Kong, China. Association for Computational Linguistics.