A cross-lingual transfer learning method for online COVID-19-related hate speech detection

doi:10.1016/j.eswa.2023.121031

	A cross-lingual transfer learning method for online COVID-19-related hate speech detection
	Liu, Lin1,2 ; Xu, Duo 3; Zhao, Pengfei 1,2; Zeng, Daniel Dajun1,2 ; Hu, Paul Jen-Hwa 5; Zhang, Qingpeng 4; Luo, Yin1,2 ; Cao, Zhidong1,2
发表期刊	EXPERT SYSTEMS WITH APPLICATIONS
ISSN	0957-4174
	2023-12-30
卷号	234 页码:11
通讯作者	Cao, Zhidong(zhidong.cao@ia.ac.cn)
摘要	During the COVID-19 pandemic, online social media platforms such as Twitter facilitate the exchange of information among people. However, the prevalence of "infodemic"such as online hate speech has exacerbated social rifts, discrimination, prejudice and even hate crimes. Timely and effective detection of the hate speech will help create a healthy public opinion environment. Most of the current COVID-19-related hate speech research focuses on a single language, such as English. In this paper, we introduce a cross-lingual transfer learning method, aiming to contribute to hate speech detection in low-resource languages. We propose a deep learning based model to classify hate speech with a pre-trained language model for multilingual text embedding. Data augmentation and cross-lingual contrastive learning are then utilized to further improve the performance of cross-lingual knowledge transfer. To evaluate our method, we collected three publicly available annotated COVID-19-related hate speech datasets on Twitter, i.e., two in English and one in German. Furthermore, a Chinese dataset based on Weibo is constructed to expand multilingual data. The experimental results across three languages illustrate the effectiveness of our method for cross-lingual hate speech detection. Test F1-scores of our method for English, Chinese, German as transfer target languages can reach up to 0.728, 0.799 and 0.612 respectively, which are on average better than other baselines.
关键词	COVID-19 Deep learning Cross-lingual Hate speech detection Natural language processing
DOI	10.1016/j.eswa.2023.121031
收录类别	SCI
语种	英语
资助项目	New Generation Artificial Intelligence Development Plan of China[2021ZD0111205] ; National Natural Science Foundation of China[72025404] ; National Natural Science Foundation of China[71621002] ; National Natural Science Foundation of China[72074209] ; Beijing Natural Science Foundation, China[L192012] ; Beijing Nova Program, China[Z201100006820085]
项目资助者	New Generation Artificial Intelligence Development Plan of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation, China ; Beijing Nova Program, China
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:001059475500001
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/53204
专题	舆论大数据科学与技术应用联合实验室
通讯作者	Cao, Zhidong
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 101408, Peoples R China 3.Beihang Univ, Sch Math Sci, Beijing 100191, Peoples R China 4.City Univ Hong Kong, Sch Data Sci, Hong Kong, Peoples R China 5.Univ Utah, David Eccles Sch Business, Salt Lake City, UT USA
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Liu, Lin,Xu, Duo,Zhao, Pengfei,et al. A cross-lingual transfer learning method for online COVID-19-related hate speech detection[J]. EXPERT SYSTEMS WITH APPLICATIONS,2023,234:11.
APA	Liu, Lin.,Xu, Duo.,Zhao, Pengfei.,Zeng, Daniel Dajun.,Hu, Paul Jen-Hwa.,...&Cao, Zhidong.(2023).A cross-lingual transfer learning method for online COVID-19-related hate speech detection.EXPERT SYSTEMS WITH APPLICATIONS,234,11.
MLA	Liu, Lin,et al."A cross-lingual transfer learning method for online COVID-19-related hate speech detection".EXPERT SYSTEMS WITH APPLICATIONS 234(2023):11.