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    <titleInfo>
        <title>Is writing style predictive of scientific fraud?</title>
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    <name type="personal">
        <namePart type="given">Chloé</namePart>
        <namePart type="family">Braud</namePart>
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    <name type="personal">
        <namePart type="given">Anders</namePart>
        <namePart type="family">Søgaard</namePart>
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        <titleInfo>
            <title>Proceedings of the Workshop on Stylistic Variation</title>
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        <name type="personal">
            <namePart type="given">Julian</namePart>
            <namePart type="family">Brooke</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Thamar</namePart>
            <namePart type="family">Solorio</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Moshe</namePart>
            <namePart type="family">Koppel</namePart>
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    <abstract>The problem of detecting scientific fraud using machine learning was recently introduced, with initial, positive results from a model taking into account various general indicators. The results seem to suggest that writing style is predictive of scientific fraud. We revisit these initial experiments, and show that the leave-one-out testing procedure they used likely leads to a slight over-estimate of the predictability, but also that simple models can outperform their proposed model by some margin. We go on to explore more abstract linguistic features, such as linguistic complexity and discourse structure, only to obtain negative results. Upon analyzing our models, we do see some interesting patterns, though: Scientific fraud, for examples, contains less comparison, as well as different types of hedging and ways of presenting logical reasoning.</abstract>
    <identifier type="citekey">braud-sogaard-2017-writing</identifier>
    <identifier type="doi">10.18653/v1/W17-4905</identifier>
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        <url>https://aclanthology.org/W17-4905</url>
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        <date>2017-09</date>
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            <start>37</start>
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%0 Conference Proceedings
%T Is writing style predictive of scientific fraud?
%A Braud, Chloé
%A Søgaard, Anders
%Y Brooke, Julian
%Y Solorio, Thamar
%Y Koppel, Moshe
%S Proceedings of the Workshop on Stylistic Variation
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F braud-sogaard-2017-writing
%X The problem of detecting scientific fraud using machine learning was recently introduced, with initial, positive results from a model taking into account various general indicators. The results seem to suggest that writing style is predictive of scientific fraud. We revisit these initial experiments, and show that the leave-one-out testing procedure they used likely leads to a slight over-estimate of the predictability, but also that simple models can outperform their proposed model by some margin. We go on to explore more abstract linguistic features, such as linguistic complexity and discourse structure, only to obtain negative results. Upon analyzing our models, we do see some interesting patterns, though: Scientific fraud, for examples, contains less comparison, as well as different types of hedging and ways of presenting logical reasoning.
%R 10.18653/v1/W17-4905
%U https://aclanthology.org/W17-4905
%U https://doi.org/10.18653/v1/W17-4905
%P 37-42

Markdown (Informal)

[Is writing style predictive of scientific fraud?](https://aclanthology.org/W17-4905) (Braud & Søgaard, Style-Var 2017)

• Is writing style predictive of scientific fraud? (Braud & Søgaard, Style-Var 2017)

ACL

• Chloé Braud and Anders Søgaard. 2017. Is writing style predictive of scientific fraud?. In Proceedings of the Workshop on Stylistic Variation, pages 37–42, Copenhagen, Denmark. Association for Computational Linguistics.