Abstract
We investigate the effect of varying citation context window sizes on model performance in citation intent classification. Prior studies have been limited to the application of fixed-size contiguous citation contexts or the use of manually curated citation contexts. We introduce a new automated unsupervised approach for the selection of a dynamic-size and potentially non-contiguous citation context, which utilises the transformer-based document representations and embedding similarities. Our experiments show that the addition of non-contiguous citing sentences improves performance beyond previous results. Evalu- ating on the (1) domain-specific (ACL-ARC) and (2) the multi-disciplinary (SDP-ACT) dataset demonstrates that the inclusion of additional context beyond the citing sentence significantly improves the citation classifi- cation model’s performance, irrespective of the dataset’s domain. We release the datasets and the source code used for the experiments at: https://github.com/oacore/dynamic_citation_context- Anthology ID:
- 2022.aacl-main.41
- Volume:
- Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
- Month:
- November
- Year:
- 2022
- Address:
- Online only
- Editors:
- Yulan He, Heng Ji, Sujian Li, Yang Liu, Chua-Hui Chang
- Venues:
- AACL | IJCNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 539–549
- Language:
- URL:
- https://aclanthology.org/2022.aacl-main.41
- DOI:
- Cite (ACL):
- Suchetha Nambanoor Kunnath, David Pride, and Petr Knoth. 2022. Dynamic Context Extraction for Citation Classification. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), pages 539–549, Online only. Association for Computational Linguistics.
- Cite (Informal):
- Dynamic Context Extraction for Citation Classification (Nambanoor Kunnath et al., AACL-IJCNLP 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.aacl-main.41.pdf