@inproceedings{fridriksdottir-etal-2024-ice,
    title = "Ice and Fire: Dataset on Sentiment, Emotions, Toxicity, Sarcasm, Hate speech, Sympathy and More in {I}celandic Blog Comments",
    author = "Fri{\dh}riksd{\'o}ttir, Steinunn Rut  and
      Simonsen, Annika  and
      {\'A}smundsson, Atli Sn{\ae}r  and
      Fri{\dh}j{\'o}nsd{\'o}ttir, Gu{\dh}r{\'u}n Lilja  and
      Ingason, Anton Karl  and
      Sn{\ae}bjarnarson, V{\'e}steinn  and
      Einarsson, Hafsteinn",
    editor = "Kumar, Ritesh  and
      Ojha, Atul Kr.  and
      Malmasi, Shervin  and
      Chakravarthi, Bharathi Raja  and
      Lahiri, Bornini  and
      Singh, Siddharth  and
      Ratan, Shyam",
    booktitle = "Proceedings of the Fourth Workshop on Threat, Aggression {\&} Cyberbullying @ LREC-COLING-2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.trac-1.9",
    pages = "73--84",
    abstract = "This study introduces {``}Ice and Fire,{''} a Multi-Task Learning (MTL) dataset tailored for sentiment analysis in the Icelandic language, encompassing a wide range of linguistic tasks, including sentiment and emotion detection, as well as identification of toxicity, hate speech, encouragement, sympathy, sarcasm/irony, and trolling. With 261 fully annotated blog comments and 1045 comments annotated in at least one task, this contribution marks a significant step forward in the field of Icelandic natural language processing. It provides a comprehensive dataset for understanding the nuances of online communication in Icelandic and an interface to expand the annotation effort. Despite the challenges inherent in subjective interpretation of text, our findings highlight the positive potential of this dataset to improve text analysis techniques and encourage more inclusive online discourse in Icelandic communities. With promising baseline performances, {``}Ice and Fire{''} sets the stage for future research to enhance automated text analysis and develop sophisticated language technologies, contributing to healthier online environments and advancing Icelandic language resources.",
}

This study introduces {``}Ice and Fire,{''} a Multi-Task Learning (MTL) dataset tailored for sentiment analysis in the Icelandic language, encompassing a wide range of linguistic tasks, including sentiment and emotion detection, as well as identification of toxicity, hate speech, encouragement, sympathy, sarcasm/irony, and trolling. With 261 fully annotated blog comments and 1045 comments annotated in at least one task, this contribution marks a significant step forward in the field of Icelandic natural language processing. It provides a comprehensive dataset for understanding the nuances of online communication in Icelandic and an interface to expand the annotation effort. Despite the challenges inherent in subjective interpretation of text, our findings highlight the positive potential of this dataset to improve text analysis techniques and encourage more inclusive online discourse in Icelandic communities. With promising baseline performances, {``}Ice and Fire{''} sets the stage for future research to enhance automated text analysis and develop sophisticated language technologies, contributing to healthier online environments and advancing Icelandic language resources.
Fri{\dh}riksd{\'o}ttir, Steinunn Rut Simonsen, Annika {\'A}smundsson, Atli Sn{\ae}r Fri{\dh}j{\'o}nsd{\'o}ttir, Gu{\dh}r{\'u}n Lilja Ingason, Anton Karl Sn{\ae}bjarnarson, V{\'e}steinn Einarsson, Hafsteinn
Ice and Fire: Dataset on Sentiment, Emotions, Toxicity, Sarcasm, Hate speech, Sympathy and More in Icelandic Blog Comments