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Expert-Annotated Dataset to Study Cyberbullying in Polish Language

Author

Listed:
  • Michal Ptaszynski

    (Text Information Processing Laboratory, Kitami Institute of Technology, Kitami 090-8507, Japan
    These authors contributed equally to this work.)

  • Agata Pieciukiewicz

    (Polish-Japanese Academy of Information Technology, 02-008 Warszawa, Poland
    These authors contributed equally to this work.)

  • Pawel Dybala

    (Institute of Middle and Far Eastern Studies, Faculty of International and Political Studies, Jagiellonian University, 30-059 Kraków, Poland
    These authors contributed equally to this work.)

  • Pawel Skrzek

    (Samurai Labs, Aleja Zwyciȩstwa 96/98, 81-451 Gdynia, Poland
    These authors contributed equally to this work.)

  • Kamil Soliwoda

    (Samurai Labs, Aleja Zwyciȩstwa 96/98, 81-451 Gdynia, Poland
    These authors contributed equally to this work.)

  • Marcin Fortuna

    (Samurai Labs, Aleja Zwyciȩstwa 96/98, 81-451 Gdynia, Poland
    Institute of English and American Studies, University of Gdańsk, ul. Bażyńskiego 8, 80-309 Gdańsk, Poland
    These authors contributed equally to this work.)

  • Gniewosz Leliwa

    (Samurai Labs, Aleja Zwyciȩstwa 96/98, 81-451 Gdynia, Poland
    These authors contributed equally to this work.)

  • Michal Wroczynski

    (Samurai Labs, Aleja Zwyciȩstwa 96/98, 81-451 Gdynia, Poland
    These authors contributed equally to this work.)

Abstract

We introduce the first dataset of harmful and offensive language collected from the Polish Internet. This dataset was meticulously curated to facilitate the exploration of harmful online phenomena such as cyberbullying and hate speech, which have exhibited a significant surge both within the Polish Internet as well as globally. The dataset was systematically collected and then annotated using two approaches. First, it was annotated by two proficient layperson volunteers, operating under the guidance of a specialist in the language of cyberbullying and hate speech. To enhance the precision of the annotations, a secondary round of annotations was carried out by a team of adept annotators with specialized long-term expertise in cyberbullying and hate speech annotations. This second phase was further overseen by an experienced annotator, acting as a super-annotator. In its initial application, the dataset was leveraged for the categorization of cyberbullying instances in the Polish language. Specifically, the dataset serves as the foundation for two distinct tasks: (1) a binary classification that segregates harmful and non-harmful messages and (2) a multi-class classification that distinguishes between two variations of harmful content (cyberbullying and hate speech), as well as a non-harmful category. Alongside the dataset itself, we also provide the models that showed satisfying classification performance. These models are made accessible for third-party use in constructing cyberbullying prevention systems.

Suggested Citation

  • Michal Ptaszynski & Agata Pieciukiewicz & Pawel Dybala & Pawel Skrzek & Kamil Soliwoda & Marcin Fortuna & Gniewosz Leliwa & Michal Wroczynski, 2023. "Expert-Annotated Dataset to Study Cyberbullying in Polish Language," Data, MDPI, vol. 9(1), pages 1-26, December.
    • Handle: RePEc:gam:jdataj:v:9:y:2023:i:1:p:1-:d:1303523
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    References listed on IDEAS

    as
    1. Arnout B. Boot & Erik Tjong Kim Sang & Katinka Dijkstra & Rolf A. Zwaan, 2019. "How character limit affects language usage in tweets," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-13, December.
    2. Michal Ptaszynski & Monika Zasko-Zielinska & Michal Marcinczuk & Gniewosz Leliwa & Marcin Fortuna & Kamil Soliwoda & Ida Dziublewska & Olimpia Hubert & Pawel Skrzek & Jan Piesiewicz & Paula Karbowska , 2021. "Looking for Razors and Needles in a Haystack: Multifaceted Analysis of Suicidal Declarations on Social Media—A Pragmalinguistic Approach," IJERPH, MDPI, vol. 18(22), pages 1-49, November.
    Full references (including those not matched with items on IDEAS)

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