Extracting Citizen Feedback from Social Media by Appraisal Opinion Type Viewpoint-Reference-Cited by-同舟云学术

Extracting Citizen Feedback from Social Media by Appraisal Opinion Type Viewpoint

Published:2022 Issue:2 Volume:29 Page:416-442
ISSN:1340-7619
Container-title:Journal of Natural Language Processing
language:en
Short-container-title:Journal of Natural Language Processing

Author:

Ishida Tetsuya¹,Seki Yohei²,Kashino Wakako³,Kando Noriko⁴

Affiliation:

1. Graduate School of Comprehensive Human Sciences, University of Tsukuba

2. Faculty of Library, Information and Media Science, University of Tsukuba

3. National Institute for Japanese Language and Linguistics

4. National Institute of Informatics

Publisher

Association for Natural Language Processing

Subject

General Earth and Planetary Sciences,General Environmental Science

Link

https://www.jstage.jst.go.jp/article/jnlp/29/2/29_416/_pdf

Reference33 articles.

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4. Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K. (2019). “BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.” In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pp. 4171–4186.

5. Dimitrov, D., Baran, E., Fafalios, P., Yu, R., Zhu, X., Zloch, M., and Dietze, S. (2020). "TweetsCOV19 - A Knowledge Base of Semantically Annotated Tweets about the COVID-19 Pandemic." In Proceedings of the 29th ACM International Conference on Information &

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