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    <titleInfo>
        <title>Clickbait in Hindi News Media : A Preliminary Study</title>
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        <namePart type="given">Vivek</namePart>
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        <namePart type="family">Vemuri</namePart>
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            <title>Proceedings of the 17th International Conference on Natural Language Processing (ICON)</title>
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            <namePart type="given">Pushpak</namePart>
            <namePart type="family">Bhattacharyya</namePart>
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            <namePart type="given">Misra</namePart>
            <namePart type="family">Sharma</namePart>
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            <namePart type="given">Rajeev</namePart>
            <namePart type="family">Sangal</namePart>
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            <publisher>NLP Association of India (NLPAI)</publisher>
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    <abstract>A corpus of Hindi news headlines shared on Twitter was created by collecting tweets of 5 mainstream Hindi news sources for a period of 4 months. 7 independent annotators were recruited to mark the 20 most retweeted news posts by each of the 5 news sources on its clickbait nature. The clickbait score hence generated was assessed for its correlation with interactions on the platform (retweets, favorites, reader replies), tweet word count, and normalized POS (part-of-speech) tag counts in tweets. A positive correlation was observed between readers’ interactions with tweets and tweets’ clickbait score. Significant correlations were also observed for POS tag counts and clickbait score. The prevalence of clickbait in mainstream Hindi news media was found to be similar to its prevalence in English news media. We hope that our observations would provide a platform for discussions on clickbait in mainstream Hindi news media.</abstract>
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        <url>https://aclanthology.org/2020.icon-main.11/</url>
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    <part>
        <date>2020-12</date>
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            <start>85</start>
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%0 Conference Proceedings
%T Clickbait in Hindi News Media : A Preliminary Study
%A Kaushal, Vivek
%A Vemuri, Kavita
%Y Bhattacharyya, Pushpak
%Y Sharma, Dipti Misra
%Y Sangal, Rajeev
%S Proceedings of the 17th International Conference on Natural Language Processing (ICON)
%D 2020
%8 December
%I NLP Association of India (NLPAI)
%C Indian Institute of Technology Patna, Patna, India
%F kaushal-vemuri-2020-clickbait
%X A corpus of Hindi news headlines shared on Twitter was created by collecting tweets of 5 mainstream Hindi news sources for a period of 4 months. 7 independent annotators were recruited to mark the 20 most retweeted news posts by each of the 5 news sources on its clickbait nature. The clickbait score hence generated was assessed for its correlation with interactions on the platform (retweets, favorites, reader replies), tweet word count, and normalized POS (part-of-speech) tag counts in tweets. A positive correlation was observed between readers’ interactions with tweets and tweets’ clickbait score. Significant correlations were also observed for POS tag counts and clickbait score. The prevalence of clickbait in mainstream Hindi news media was found to be similar to its prevalence in English news media. We hope that our observations would provide a platform for discussions on clickbait in mainstream Hindi news media.
%U https://aclanthology.org/2020.icon-main.11/
%P 85-89

Markdown (Informal)

[Clickbait in Hindi News Media : A Preliminary Study](https://aclanthology.org/2020.icon-main.11/) (Kaushal & Vemuri, ICON 2020)

• Clickbait in Hindi News Media : A Preliminary Study (Kaushal & Vemuri, ICON 2020)

ACL

• Vivek Kaushal and Kavita Vemuri. 2020. Clickbait in Hindi News Media : A Preliminary Study. In Proceedings of the 17th International Conference on Natural Language Processing (ICON), pages 85–89, Indian Institute of Technology Patna, Patna, India. NLP Association of India (NLPAI).