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    <abstract>Text-based emotion detection is crucial in NLP,with applications in sentiment analysis, socialmedia monitoring, and human-computer interaction. This paper presents our approach tothe Multi-label Emotion Detection challenge,classifying texts into joy, sadness, anger, fear,and surprise. We experimented with traditionalmachine learning and transformer-based models, but results were suboptimal: F1 scores of0.3723 (English), 0.5174 (German), and 0.6957(Spanish). We analyze the impact of preprocessing, model selection, and dataset characteristics, highlighting key challenges in multilabel emotion classification and potential improvements.</abstract>
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%0 Conference Proceedings
%T DataBees at SemEval-2025 Task 11: Challenges and Limitations in Multi-Label Emotion Detection
%A Anand, Sowmya
%A Sriram, Tanisha
%A Sivanaiah, Rajalakshmi
%A S, Angel Deborah
%A Thankanadar, Mirnalinee
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F anand-etal-2025-databees
%X Text-based emotion detection is crucial in NLP,with applications in sentiment analysis, socialmedia monitoring, and human-computer interaction. This paper presents our approach tothe Multi-label Emotion Detection challenge,classifying texts into joy, sadness, anger, fear,and surprise. We experimented with traditionalmachine learning and transformer-based models, but results were suboptimal: F1 scores of0.3723 (English), 0.5174 (German), and 0.6957(Spanish). We analyze the impact of preprocessing, model selection, and dataset characteristics, highlighting key challenges in multilabel emotion classification and potential improvements.
%U https://aclanthology.org/2025.semeval-1.33/
%P 222-227

Markdown (Informal)

[DataBees at SemEval-2025 Task 11: Challenges and Limitations in Multi-Label Emotion Detection](https://aclanthology.org/2025.semeval-1.33/) (Anand et al., SemEval 2025)

• DataBees at SemEval-2025 Task 11: Challenges and Limitations in Multi-Label Emotion Detection (Anand et al., SemEval 2025)

ACL

• Sowmya Anand, Tanisha Sriram, Rajalakshmi Sivanaiah, Angel Deborah S, and Mirnalinee Thankanadar. 2025. DataBees at SemEval-2025 Task 11: Challenges and Limitations in Multi-Label Emotion Detection. In Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025), pages 222–227, Vienna, Austria. Association for Computational Linguistics.