
Shared task for cross-lingual classification of Corporate Social Responsibility (CSR) themes and topics
- Author
- Yola Nayekoo, Sophia Katrenko, Veronique Hoste (UGent) , Aaron Maladry (UGent) and Els Lefever (UGent)
- Organization
- Abstract
- This paper provides an overview of the Shared Task for Cross-lingual Classification of CSR Themes and Topics. We framed the task as two separate sub-tasks: one cross-lingual multi-class CSR theme recognition task for English, French and simplified Chinese and one multi-label fine-grained classification task of CSR topics for Environment (ENV) and Labor and Human Rights (LAB) themes in English. The participants were provided with URLs and annotations for both tasks. Several teams downloaded the data, of which two teams submitted a system for both sub-tasks. In this overview paper, we discuss the set-up of the task and our main findings.
- Keywords
- multilingual CSR, multi-label classification, CSR theme detection
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01J0G4NENDAKW4KNEH44AH5AJK
- MLA
- Nayekoo, Yola, et al. “Shared Task for Cross-Lingual Classification of Corporate Social Responsibility (CSR) Themes and Topics.” Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing, edited by Chung-Chi Chen et al., Association for Computational Linguistics (ACL), 2024, pp. 283–91.
- APA
- Nayekoo, Y., Katrenko, S., Hoste, V., Maladry, A., & Lefever, E. (2024). Shared task for cross-lingual classification of Corporate Social Responsibility (CSR) themes and topics. In C.-C. Chen, Z. Ma, & U. Hahn (Eds.), Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing (pp. 283–291). Association for Computational Linguistics (ACL).
- Chicago author-date
- Nayekoo, Yola, Sophia Katrenko, Veronique Hoste, Aaron Maladry, and Els Lefever. 2024. “Shared Task for Cross-Lingual Classification of Corporate Social Responsibility (CSR) Themes and Topics.” In Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing, edited by Chung-Chi Chen, Zhiqiang Ma, and Udo Hahn, 283–91. Association for Computational Linguistics (ACL).
- Chicago author-date (all authors)
- Nayekoo, Yola, Sophia Katrenko, Veronique Hoste, Aaron Maladry, and Els Lefever. 2024. “Shared Task for Cross-Lingual Classification of Corporate Social Responsibility (CSR) Themes and Topics.” In Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing, ed by. Chung-Chi Chen, Zhiqiang Ma, and Udo Hahn, 283–291. Association for Computational Linguistics (ACL).
- Vancouver
- 1.Nayekoo Y, Katrenko S, Hoste V, Maladry A, Lefever E. Shared task for cross-lingual classification of Corporate Social Responsibility (CSR) themes and topics. In: Chen C-C, Ma Z, Hahn U, editors. Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing. Association for Computational Linguistics (ACL); 2024. p. 283–91.
- IEEE
- [1]Y. Nayekoo, S. Katrenko, V. Hoste, A. Maladry, and E. Lefever, “Shared task for cross-lingual classification of Corporate Social Responsibility (CSR) themes and topics,” in Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing, 2024, pp. 283–291.
@inproceedings{01J0G4NENDAKW4KNEH44AH5AJK, abstract = {{This paper provides an overview of the Shared Task for Cross-lingual Classification of CSR Themes and Topics. We framed the task as two separate sub-tasks: one cross-lingual multi-class CSR theme recognition task for English, French and simplified Chinese and one multi-label fine-grained classification task of CSR topics for Environment (ENV) and Labor and Human Rights (LAB) themes in English. The participants were provided with URLs and annotations for both tasks. Several teams downloaded the data, of which two teams submitted a system for both sub-tasks. In this overview paper, we discuss the set-up of the task and our main findings.}}, author = {{Nayekoo, Yola and Katrenko, Sophia and Hoste, Veronique and Maladry, Aaron and Lefever, Els}}, booktitle = {{Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing}}, editor = {{Chen, Chung-Chi and Ma, Zhiqiang and Hahn, Udo}}, isbn = {{9782493814197}}, issn = {{2522-2686}}, keywords = {{multilingual CSR,multi-label classification,CSR theme detection}}, language = {{eng}}, pages = {{283--291}}, publisher = {{Association for Computational Linguistics (ACL)}}, title = {{Shared task for cross-lingual classification of Corporate Social Responsibility (CSR) themes and topics}}, url = {{https://aclanthology.org/2024.finnlp-1.32}}, year = {{2024}}, }