Target-based Sentiment Annotation in Chinese Financial News
Chaofa Yuan, Yuhan Liu, Rongdi Yin, Jun Zhang, Qinling Zhu, Ruibin Mao, Ruifeng Xu
Abstract
This paper presents the design and construction of a large-scale target-based sentiment annotation corpus on Chinese financial news text. Different from the most existing paragraph/document-based annotation corpus, in this study, target-based fine-grained sentiment annotation is performed. The companies, brands and other financial entities are regarded as the targets. The clause reflecting the profitability, loss or other business status of financial entities is regarded as the sentiment expression for determining the polarity. Based on high quality annotation guideline and effective quality control strategy, a corpus with 8,314 target-level sentiment annotation is constructed on 6,336 paragraphs from Chinese financial news text. Based on this corpus, several state-of-the-art sentiment analysis models are evaluated.- Anthology ID:
- 2020.lrec-1.620
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 5040–5045
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.620
- DOI:
- Cite (ACL):
- Chaofa Yuan, Yuhan Liu, Rongdi Yin, Jun Zhang, Qinling Zhu, Ruibin Mao, and Ruifeng Xu. 2020. Target-based Sentiment Annotation in Chinese Financial News. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 5040–5045, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Target-based Sentiment Annotation in Chinese Financial News (Yuan et al., LREC 2020)
- PDF:
- https://preview.aclanthology.org/naacl-24-ws-corrections/2020.lrec-1.620.pdf