Correct Metadata for
Abstract
The way we use words is influenced by our opinion. We investigate whether this is reflected in contextualized word embeddings. For example, is the representation of “animal” different between people who would abolish zoos and those who would not? We explore this question from a Lexical Semantic Change standpoint. Our experiments with BERT embeddings derived from datasets with stance annotations reveal small but significant differences in word representations between opposing stances.- Anthology ID:
- 2022.coling-1.347
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 3950–3959
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.347/
- DOI:
- Bibkey:
- Cite (ACL):
- Aina Garí Soler, Matthieu Labeau, and Chloé Clavel. 2022. One Word, Two Sides: Traces of Stance in Contextualized Word Representations. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3950–3959, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- One Word, Two Sides: Traces of Stance in Contextualized Word Representations (Garí Soler et al., COLING 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.347.pdf
- Code
- ainagari/1word2sides
Export citation
@inproceedings{gari-soler-etal-2022-one, title = "One Word, Two Sides: Traces of Stance in Contextualized Word Representations", author = "Gar{\'i} Soler, Aina and Labeau, Matthieu and Clavel, Chlo{\'e}", editor = "Calzolari, Nicoletta and Huang, Chu-Ren and Kim, Hansaem and Pustejovsky, James and Wanner, Leo and Choi, Key-Sun and Ryu, Pum-Mo and Chen, Hsin-Hsi and Donatelli, Lucia and Ji, Heng and Kurohashi, Sadao and Paggio, Patrizia and Xue, Nianwen and Kim, Seokhwan and Hahm, Younggyun and He, Zhong and Lee, Tony Kyungil and Santus, Enrico and Bond, Francis and Na, Seung-Hoon", booktitle = "Proceedings of the 29th International Conference on Computational Linguistics", month = oct, year = "2022", address = "Gyeongju, Republic of Korea", publisher = "International Committee on Computational Linguistics", url = "https://aclanthology.org/2022.coling-1.347/", pages = "3950--3959", abstract = "The way we use words is influenced by our opinion. We investigate whether this is reflected in contextualized word embeddings. For example, is the representation of {\textquotedblleft}animal{\textquotedblright} different between people who would abolish zoos and those who would not? We explore this question from a Lexical Semantic Change standpoint. Our experiments with BERT embeddings derived from datasets with stance annotations reveal small but significant differences in word representations between opposing stances." }
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%0 Conference Proceedings %T One Word, Two Sides: Traces of Stance in Contextualized Word Representations %A Garí Soler, Aina %A Labeau, Matthieu %A Clavel, Chloé %Y Calzolari, Nicoletta %Y Huang, Chu-Ren %Y Kim, Hansaem %Y Pustejovsky, James %Y Wanner, Leo %Y Choi, Key-Sun %Y Ryu, Pum-Mo %Y Chen, Hsin-Hsi %Y Donatelli, Lucia %Y Ji, Heng %Y Kurohashi, Sadao %Y Paggio, Patrizia %Y Xue, Nianwen %Y Kim, Seokhwan %Y Hahm, Younggyun %Y He, Zhong %Y Lee, Tony Kyungil %Y Santus, Enrico %Y Bond, Francis %Y Na, Seung-Hoon %S Proceedings of the 29th International Conference on Computational Linguistics %D 2022 %8 October %I International Committee on Computational Linguistics %C Gyeongju, Republic of Korea %F gari-soler-etal-2022-one %X The way we use words is influenced by our opinion. We investigate whether this is reflected in contextualized word embeddings. For example, is the representation of “animal” different between people who would abolish zoos and those who would not? We explore this question from a Lexical Semantic Change standpoint. Our experiments with BERT embeddings derived from datasets with stance annotations reveal small but significant differences in word representations between opposing stances. %U https://aclanthology.org/2022.coling-1.347/ %P 3950-3959
Markdown (Informal)
[One Word, Two Sides: Traces of Stance in Contextualized Word Representations](https://aclanthology.org/2022.coling-1.347/) (Garí Soler et al., COLING 2022)
- One Word, Two Sides: Traces of Stance in Contextualized Word Representations (Garí Soler et al., COLING 2022)
ACL
- Aina Garí Soler, Matthieu Labeau, and Chloé Clavel. 2022. One Word, Two Sides: Traces of Stance in Contextualized Word Representations. In Proceedings of the 29th International Conference on Computational Linguistics, pages 3950–3959, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.