Detecting Chinese Fake News on Twitter during the COVID-19 Pandemic

04/07/2023
by   Yongjun Zhang, et al.
0

The outbreak of COVID-19 has led to a global surge of Sinophobia partly because of the spread of misinformation, disinformation, and fake news on China. In this paper, we report on the creation of a novel classifier that detects whether Chinese-language social media posts from Twitter are related to fake news about China. The classifier achieves an F1 score of 0.64 and an accuracy rate of 93 with 18,425 tweets for researchers to study fake news in the Chinese language during the COVID-19 pandemic. We also introduce a new dataset generated by our classifier that tracks the dynamics of fake news in the Chinese language during the early pandemic.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/17/2021

Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News Detection

As the COVID-19 pandemic sweeps across the world, it has been accompanie...
research
02/10/2022

Understanding Twitters behavior during the pandemic: Fake News and Fear

The outbreak of the SARS-CoV-2 novel coronavirus (COVID-19) has been acc...
research
06/12/2023

LTCR: Long-Text Chinese Rumor Detection Dataset

False information can spread quickly on social media, negatively influen...
research
01/11/2021

Evaluating Deep Learning Approaches for Covid19 Fake News Detection

Social media platforms like Facebook, Twitter, and Instagram have enable...
research
03/22/2022

Are You Misinformed? A Study of Covid-Related Fake News in Bengali on Facebook

Our opinions and views of life can be shaped by how we perceive the opin...
research
05/08/2020

Detecting East Asian Prejudice on Social Media

The outbreak of COVID-19 has transformed societies across the world as g...
research
07/01/2021

Tackling COVID-19 Infodemic using Deep Learning

Humanity is battling one of the most deleterious virus in modern history...

Please sign up or login with your details

Forgot password? Click here to reset