Analyzing the Intensity of Complaints on Social Media

Ming Fang, Shi Zong, Jing Li, Xinyu Dai, Shujian Huang, Jiajun Chen

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Original language	English
Title of host publication	Findings of the Association for Computational Linguistics: NAACL 2022
Publisher	Association for Computational Linguistics (ACL)
Pages	1742-1754
DOIs	https://doi.org/10.18653/v1/2022.findings-naacl.132
Publication status	Published - Jul 2022

More information

@inproceedings{6fcfe4b57ee74ff9b477951215c6a9c3,

title = "Analyzing the Intensity of Complaints on Social Media",

author = "Ming Fang and Shi Zong and Jing Li and Xinyu Dai and Shujian Huang and Jiajun Chen",

year = "2022",

month = jul,

doi = "10.18653/v1/2022.findings-naacl.132",

language = "English",

pages = "1742--1754",

booktitle = "Findings of the Association for Computational Linguistics: NAACL 2022",

publisher = "Association for Computational Linguistics (ACL)",

}

Analyzing the Intensity of Complaints on Social Media. / Fang, Ming; Zong, Shi; Li, Jing et al.
Findings of the Association for Computational Linguistics: NAACL 2022. Association for Computational Linguistics (ACL), 2022. p. 1742-1754.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Analyzing the Intensity of Complaints on Social Media

AU - Fang, Ming

AU - Zong, Shi

AU - Li, Jing

AU - Dai, Xinyu

AU - Huang, Shujian

AU - Chen, Jiajun

PY - 2022/7

Y1 - 2022/7

U2 - 10.18653/v1/2022.findings-naacl.132

DO - 10.18653/v1/2022.findings-naacl.132

M3 - Conference article published in proceeding or book

SP - 1742

EP - 1754

BT - Findings of the Association for Computational Linguistics: NAACL 2022

PB - Association for Computational Linguistics (ACL)

ER -