Abstract
In multi-sense word embeddings, contextual variations in corpus may cause a univocal word to be embedded into different sense vectors. Shi et al. (2016) show that this kind of pseudo multi-senses can be eliminated by linear transformations. In this paper, we show that pseudo multi-senses may come from a uniform and meaningful phenomenon such as subjective and sentimental usage, though they are seemingly redundant. In this paper, we present an unsupervised algorithm to find a linear transformation which can minimize the transformed distance of a group of sense pairs. The major shrinking direction of this transformation is found to be related with subjective shift. Therefore, we can not only eliminate pseudo multi-senses in multisense embeddings, but also identify these subjective senses and tag the subjective and sentimental usage of words in the corpus automatically.- Anthology ID:
- W18-6203
- Volume:
- Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
- Month:
- October
- Year:
- 2018
- Address:
- Brussels, Belgium
- Editors:
- Alexandra Balahur, Saif M. Mohammad, Veronique Hoste, Roman Klinger
- Venue:
- WASSA
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 8–13
- Language:
- URL:
- https://aclanthology.org/W18-6203
- DOI:
- 10.18653/v1/W18-6203
- Cite (ACL):
- Yuqi Sun, Haoyue Shi, and Junfeng Hu. 2018. Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings. In Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 8–13, Brussels, Belgium. Association for Computational Linguistics.
- Cite (Informal):
- Implicit Subjective and Sentimental Usages in Multi-sense Word Embeddings (Sun et al., WASSA 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W18-6203.pdf
- Data
- MPQA Opinion Corpus