A Study of Cantonese Covid-19 Fake News Detection on Social Media

Ziwei WANG, Minzhu Zhao, Yu Chen, Yunya SONG, Liang LAN*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

With the prevalence of social media, fake news has become one of the greatest challenges in journalism, which has weakened public trust in news outlets and authorities. During the COVID-19 epidemic, the widely circulated pandemic-related fake news on social media misleads or threatens the public. Recent works have investigated fake news detection on social platforms in English and Mandarin, though Cantonese fake news has been understudied. To pave the way for Cantonese COVID-19 fake news detection, we first presented an annotated COVID-19 related Cantonese fake news dataset collected from a popular local discussion forum in Hong Kong. Then, we explored the dataset by applying topic modeling to identify the topics that contain the most significant amount of fake news. Moreover, we evaluated both traditional machine learning algorithms and deep learning algorithms for Cantonese fake news detection. Our empirical results show that deep learning based methods perform slightly better than traditional machine learning methods on TF-IDF features.
Original languageEnglish
Title of host publicationIEEE International Conference on Big Data 2021
EditorsYixin Chen, Heiko Ludwig, Yicheng Tu, Usama Fayyad, Xingquan Zhu, Xiaohua Tony Hu, Suren Byna, Xiong Liu, Jianping Zhang, Shirui Pan, Vagelis Papalexakis, Jianwu Wang, Alfredo Cuzzocrea, Carlos Ordonez
Pages6052-6054
Number of pages3
ISBN (Electronic)9781665439022
DOIs
Publication statusPublished - Dec 2021
EventIEEE International Conference on Big Data 2021 - Orlando, Florida, United States
Duration: 15 Dec 202118 Dec 2021

Publication series

NameProceedings - 2021 IEEE International Conference on Big Data, Big Data 2021

Conference

ConferenceIEEE International Conference on Big Data 2021
Country/TerritoryUnited States
CityOrlando, Florida
Period15/12/2118/12/21

Scopus Subject Areas

  • Information Systems and Management
  • Artificial Intelligence
  • Information Systems
  • Computer Vision and Pattern Recognition

User-Defined Keywords

  • Cantonese Text Analytics
  • Fake News Detection
  • Topic Modeling

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