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    <abstract>This paper presents Hotter and Colder, a dataset designed to analyze various types of online behavior in Icelandic blog comments. Building on previous work, we used GPT-4o mini to annotate approximately 800,000 comments for 25 tasks, including sentiment analysis, emotion detection, hate speech, and group generalizations. Each comment was automatically labeled on a 5-point Likert scale. In a second annotation stage, comments with high or low probabilities of containing each examined behavior were subjected to manual revision. By leveraging crowdworkers to refine these automatically labeled comments, we ensure the quality and accuracy of our dataset resulting in 12,232 uniquely annotated comments and 19,301 annotations. Hotter and Colder provides an essential resource for advancing research in content moderation and automatically detectiong harmful online behaviors in Icelandic. We release both the dataset and annotation interface.</abstract>
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%0 Conference Proceedings
%T Hotter and Colder: A New Approach to Annotating Sentiment, Emotions, and Bias in Icelandic Blog Comments
%A Fri\dhriksdóttir, Steinunn Rut
%A Saattrup Nielsen, Dan
%A Einarsson, Hafsteinn
%Y Johansson, Richard
%Y Stymne, Sara
%S Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025)
%D 2025
%8 March
%I University of Tartu Library
%C Tallinn, Estonia
%@ 978-9908-53-109-0
%F fridriksdottir-etal-2025-hotter
%X This paper presents Hotter and Colder, a dataset designed to analyze various types of online behavior in Icelandic blog comments. Building on previous work, we used GPT-4o mini to annotate approximately 800,000 comments for 25 tasks, including sentiment analysis, emotion detection, hate speech, and group generalizations. Each comment was automatically labeled on a 5-point Likert scale. In a second annotation stage, comments with high or low probabilities of containing each examined behavior were subjected to manual revision. By leveraging crowdworkers to refine these automatically labeled comments, we ensure the quality and accuracy of our dataset resulting in 12,232 uniquely annotated comments and 19,301 annotations. Hotter and Colder provides an essential resource for advancing research in content moderation and automatically detectiong harmful online behaviors in Icelandic. We release both the dataset and annotation interface.
%U https://aclanthology.org/2025.nodalida-1.18/
%P 181-191

Markdown (Informal)

[Hotter and Colder: A New Approach to Annotating Sentiment, Emotions, and Bias in Icelandic Blog Comments](https://aclanthology.org/2025.nodalida-1.18/) (Friðriksdóttir et al., NoDaLiDa 2025)

• Hotter and Colder: A New Approach to Annotating Sentiment, Emotions, and Bias in Icelandic Blog Comments (Friðriksdóttir et al., NoDaLiDa 2025)

ACL

• Steinunn Rut Friðriksdóttir, Dan Saattrup Nielsen, and Hafsteinn Einarsson. 2025. Hotter and Colder: A New Approach to Annotating Sentiment, Emotions, and Bias in Icelandic Blog Comments. In Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025), pages 181–191, Tallinn, Estonia. University of Tartu Library.