Atli Snær Ásmundsson


2024

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Ice and Fire: Dataset on Sentiment, Emotions, Toxicity, Sarcasm, Hate speech, Sympathy and More in Icelandic Blog Comments
Steinunn Rut Friðriksdóttir | Annika Simonsen | Atli Snær Ásmundsson | Guðrún Lilja Friðjónsdóttir | Anton Karl Ingason | Vésteinn Snæbjarnarson | Hafsteinn Einarsson
Proceedings of the Fourth Workshop on Threat, Aggression & Cyberbullying @ LREC-COLING-2024

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.