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    <titleInfo>
        <title>Covid or not Covid? Topic Shift in Information Cascades on Twitter</title>
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    <name type="personal">
        <namePart type="given">Liana</namePart>
        <namePart type="family">Ermakova</namePart>
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    <name type="personal">
        <namePart type="given">Diana</namePart>
        <namePart type="family">Nurbakova</namePart>
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    <name type="personal">
        <namePart type="given">Irina</namePart>
        <namePart type="family">Ovchinnikova</namePart>
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        <dateIssued>2020-12</dateIssued>
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            <title>Proceedings of the 3rd International Workshop on Rumours and Deception in Social Media (RDSM)</title>
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        <name type="personal">
            <namePart type="given">Ahmet</namePart>
            <namePart type="family">Aker</namePart>
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        <name type="personal">
            <namePart type="given">Arkaitz</namePart>
            <namePart type="family">Zubiaga</namePart>
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    <abstract>Social media have become a valuable source of information. However, its power to shape public opinion can be dangerous, especially in the case of misinformation. The existing studies on misinformation detection hypothesise that the initial message is fake. In contrast, we focus on information distortion occurring in cascades as the initial message is quoted or receives a reply. We show a significant topic shift in information cascades on Twitter during the Covid-19 pandemic providing valuable insights for the automatic analysis of information distortion.</abstract>
    <identifier type="citekey">ermakova-etal-2020-covid</identifier>
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        <url>https://aclanthology.org/2020.rdsm-1.3</url>
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    <part>
        <date>2020-12</date>
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            <start>32</start>
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%0 Conference Proceedings
%T Covid or not Covid? Topic Shift in Information Cascades on Twitter
%A Ermakova, Liana
%A Nurbakova, Diana
%A Ovchinnikova, Irina
%Y Aker, Ahmet
%Y Zubiaga, Arkaitz
%S Proceedings of the 3rd International Workshop on Rumours and Deception in Social Media (RDSM)
%D 2020
%8 December
%I Association for Computational Linguistics
%C Barcelona, Spain (Online)
%F ermakova-etal-2020-covid
%X Social media have become a valuable source of information. However, its power to shape public opinion can be dangerous, especially in the case of misinformation. The existing studies on misinformation detection hypothesise that the initial message is fake. In contrast, we focus on information distortion occurring in cascades as the initial message is quoted or receives a reply. We show a significant topic shift in information cascades on Twitter during the Covid-19 pandemic providing valuable insights for the automatic analysis of information distortion.
%U https://aclanthology.org/2020.rdsm-1.3
%P 32-37

Markdown (Informal)

[Covid or not Covid? Topic Shift in Information Cascades on Twitter](https://aclanthology.org/2020.rdsm-1.3) (Ermakova et al., RDSM 2020)

• Covid or not Covid? Topic Shift in Information Cascades on Twitter (Ermakova et al., RDSM 2020)

ACL

• Liana Ermakova, Diana Nurbakova, and Irina Ovchinnikova. 2020. Covid or not Covid? Topic Shift in Information Cascades on Twitter. In Proceedings of the 3rd International Workshop on Rumours and Deception in Social Media (RDSM), pages 32–37, Barcelona, Spain (Online). Association for Computational Linguistics.