ROCLING-2025 Shared Task: Chinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts

Lung - Hao Lee; Tzu-Mi Lin; Hsiu-Min Shih; Kuo-Kai Shyu; Anna S. Hsu; Peih-Ying Lu

ROCLING-2025 Shared Task: Chinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts

Lung-Hao Lee, Tzu-Mi Lin, Hsiu-Min Shih, Kuo-Kai Shyu, Anna S. Hsu, Peih-Ying Lu

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Abstract

This paper describes the ROCLING-2025 shared task aimed at Chinese dimensional sentiment analysis for medical self-refection texts, including task organization, data preparation, performance metrics, and evaluation results. A total of six participating teams submitted results for techniques developed for valence-arousal intensity prediction. All datasets with gold standards and evaluation scripts used in this shared task are publicly available online for further research.

Anthology ID:: 2025.rocling-main.41
Volume:: Proceedings of the 37th Conference on Computational Linguistics and Speech Processing (ROCLING 2025)
Month:: November
Year:: 2025
Address:: National Taiwan University, Taipei City, Taiwan
Editors:: Kai-Wei Chang, Ke-Han Lu, Chih-Kai Yang, Zhi-Rui Tam, Wen-Yu Chang, Chung-Che Wang
Venue:: ROCLING
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 375–380
Language:
URL:: https://aclanthology.org/2025.rocling-main.41/
DOI:
Bibkey:
Cite (ACL):: Lung-Hao Lee, Tzu-Mi Lin, Hsiu-Min Shih, Kuo-Kai Shyu, Anna S. Hsu, and Peih-Ying Lu. 2025. ROCLING-2025 Shared Task: Chinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts. In Proceedings of the 37th Conference on Computational Linguistics and Speech Processing (ROCLING 2025), pages 375–380, National Taiwan University, Taipei City, Taiwan. Association for Computational Linguistics.
Cite (Informal):: ROCLING-2025 Shared Task: Chinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts (Lee et al., ROCLING 2025)
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PDF:: https://aclanthology.org/2025.rocling-main.41.pdf

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@inproceedings{lee-etal-2025-rocling,
    title = "{ROCLING}-2025 Shared Task: {C}hinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts",
    author = "Lee, Lung-Hao  and
      Lin, Tzu-Mi  and
      Shih, Hsiu-Min  and
      Shyu, Kuo-Kai  and
      Hsu, Anna S.  and
      Lu, Peih-Ying",
    editor = "Chang, Kai-Wei  and
      Lu, Ke-Han  and
      Yang, Chih-Kai  and
      Tam, Zhi-Rui  and
      Chang, Wen-Yu  and
      Wang, Chung-Che",
    booktitle = "Proceedings of the 37th Conference on Computational Linguistics and Speech Processing (ROCLING 2025)",
    month = nov,
    year = "2025",
    address = "National Taiwan University, Taipei City, Taiwan",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.rocling-main.41/",
    pages = "375--380",
    ISBN = "979-8-89176-379-1",
    abstract = "This paper describes the ROCLING-2025 shared task aimed at Chinese dimensional sentiment analysis for medical self-refection texts, including task organization, data preparation, performance metrics, and evaluation results. A total of six participating teams submitted results for techniques developed for valence-arousal intensity prediction. All datasets with gold standards and evaluation scripts used in this shared task are publicly available online for further research."
}

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%0 Conference Proceedings
%T ROCLING-2025 Shared Task: Chinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts
%A Lee, Lung-Hao
%A Lin, Tzu-Mi
%A Shih, Hsiu-Min
%A Shyu, Kuo-Kai
%A Hsu, Anna S.
%A Lu, Peih-Ying
%Y Chang, Kai-Wei
%Y Lu, Ke-Han
%Y Yang, Chih-Kai
%Y Tam, Zhi-Rui
%Y Chang, Wen-Yu
%Y Wang, Chung-Che
%S Proceedings of the 37th Conference on Computational Linguistics and Speech Processing (ROCLING 2025)
%D 2025
%8 November
%I Association for Computational Linguistics
%C National Taiwan University, Taipei City, Taiwan
%@ 979-8-89176-379-1
%F lee-etal-2025-rocling
%X This paper describes the ROCLING-2025 shared task aimed at Chinese dimensional sentiment analysis for medical self-refection texts, including task organization, data preparation, performance metrics, and evaluation results. A total of six participating teams submitted results for techniques developed for valence-arousal intensity prediction. All datasets with gold standards and evaluation scripts used in this shared task are publicly available online for further research.
%U https://aclanthology.org/2025.rocling-main.41/
%P 375-380

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Markdown (Informal)

[ROCLING-2025 Shared Task: Chinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts](https://aclanthology.org/2025.rocling-main.41/) (Lee et al., ROCLING 2025)

ROCLING-2025 Shared Task: Chinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts (Lee et al., ROCLING 2025)

ACL

Lung-Hao Lee, Tzu-Mi Lin, Hsiu-Min Shih, Kuo-Kai Shyu, Anna S. Hsu, and Peih-Ying Lu. 2025. ROCLING-2025 Shared Task: Chinese Dimensional Sentiment Analysis for Medical Self-Reflection Texts. In Proceedings of the 37th Conference on Computational Linguistics and Speech Processing (ROCLING 2025), pages 375–380, National Taiwan University, Taipei City, Taiwan. Association for Computational Linguistics.