Shared task for cross-lingual classification of Corporate Social Responsibility (CSR) themes and topics

Publication type
C1
Publication status
Published
Authors
Nayekoo, Y., Katrenko, S., Hoste, V., Maladry, A, & Lefever, E.
Editor
Chung-Chi Chen, Zhiqiang Ma and Udo Hahn
Series
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
Pagination
283-291
Publisher
Association for Computational Linguistics (ACL)
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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.