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        <title>Data Set for Stance and Sentiment Analysis from User Comments on Croatian News</title>
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            <title>Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing</title>
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        <name type="personal">
            <namePart type="given">Tomaž</namePart>
            <namePart type="family">Erjavec</namePart>
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            <namePart type="given">Michał</namePart>
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    <abstract>Nowadays it is becoming more important than ever to find new ways of extracting useful information from the evergrowing amount of user-generated data available online. In this paper, we describe the creation of a data set that contains news articles and corresponding comments from Croatian news outlet 24 sata. Our annotation scheme is specifically tailored for the task of detecting stances and sentiment from user comments as well as assessing if commentator claims are verifiable. Through this data, we hope to get a better understanding of the publics viewpoint on various events. In addition, we also explore the potential of applying supervised machine learning models toautomate annotation of more data.</abstract>
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    <identifier type="doi">10.18653/v1/W19-3707</identifier>
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%0 Conference Proceedings
%T Data Set for Stance and Sentiment Analysis from User Comments on Croatian News
%A Bošnjak, Mihaela
%A Karan, Vanja Mladen
%Y Erjavec, Tomaž
%Y Marcińczuk, Michał
%Y Nakov, Preslav
%Y Piskorski, Jakub
%Y Pivovarova, Lidia
%Y Šnajder, Jan
%Y Steinberger, Josef
%Y Yangarber, Roman
%S Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F bosnjak-karan-2019-data
%X Nowadays it is becoming more important than ever to find new ways of extracting useful information from the evergrowing amount of user-generated data available online. In this paper, we describe the creation of a data set that contains news articles and corresponding comments from Croatian news outlet 24 sata. Our annotation scheme is specifically tailored for the task of detecting stances and sentiment from user comments as well as assessing if commentator claims are verifiable. Through this data, we hope to get a better understanding of the publics viewpoint on various events. In addition, we also explore the potential of applying supervised machine learning models toautomate annotation of more data.
%R 10.18653/v1/W19-3707
%U https://aclanthology.org/W19-3707/
%U https://doi.org/10.18653/v1/W19-3707
%P 50-55

Markdown (Informal)

[Data Set for Stance and Sentiment Analysis from User Comments on Croatian News](https://aclanthology.org/W19-3707/) (Bošnjak & Karan, BSNLP 2019)

• Data Set for Stance and Sentiment Analysis from User Comments on Croatian News (Bošnjak & Karan, BSNLP 2019)

ACL

• Mihaela Bošnjak and Vanja Mladen Karan. 2019. Data Set for Stance and Sentiment Analysis from User Comments on Croatian News. In Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing, pages 50–55, Florence, Italy. Association for Computational Linguistics.