@inproceedings{muthya-sudheendra-etal-2024-skotapa,
    title = "{S}k{OT}a{PA}: A Dataset for Skepticism Detection in Online Text after Persuasion Attempt",
    author = "Muthya Sudheendra, Smitha  and
      Abdollahi, Maral  and
      Kang, Dongyeop  and
      Huh, Jisu  and
      Srivastava, Jaideep",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.1295",
    pages = "14871--14876",
    abstract = "Individuals often encounter persuasion attempts, during which a persuasion agent aims to persuade a target to change the target{'}s emotions, beliefs, and behaviors. These persuasion attempts can be observed in various social settings, such as advertising, public health, political campaigns, and personal relationships. During these persuasion attempts, targets generally like to preserve their autonomy, so their responses often manifest in some form of resistance, like a skeptical reaction. In order to detect such skepticism in response to persuasion attempts on social media, we developed a corpus based on consumer psychology. In this paper, we consider one of the most prominent areas in which persuasion attempts unfold: social media influencer marketing. In this paper, we introduce the skepticism detection corpus, SkOTaPA, which was developed using multiple independent human annotations, and inter-coder reliability was evaluated with Krippendorff{'}s alpha (0.709). We performed validity tests to show skepticism cannot be detected using other potential proxy variables like sentiment and sarcasm.",
}

Individuals often encounter persuasion attempts, during which a persuasion agent aims to persuade a target to change the target{'}s emotions, beliefs, and behaviors. These persuasion attempts can be observed in various social settings, such as advertising, public health, political campaigns, and personal relationships. During these persuasion attempts, targets generally like to preserve their autonomy, so their responses often manifest in some form of resistance, like a skeptical reaction. In order to detect such skepticism in response to persuasion attempts on social media, we developed a corpus based on consumer psychology. In this paper, we consider one of the most prominent areas in which persuasion attempts unfold: social media influencer marketing. In this paper, we introduce the skepticism detection corpus, SkOTaPA, which was developed using multiple independent human annotations, and inter-coder reliability was evaluated with Krippendorff{'}s alpha (0.709). We performed validity tests to show skepticism cannot be detected using other potential proxy variables like sentiment and sarcasm.
Muthya Sudheendra, Smitha Abdollahi, Maral Kang, Dongyeop Huh, Jisu Srivastava, Jaideep
SkOTaPA: A Dataset for Skepticism Detection in Online Text after Persuasion Attempt