Detecting Propaganda on the Sentence Level during the COVID-19 Pandemic

• URL: http://arxiv.org/abs/2108.12269v1
• Date: Sat, 31 Jul 2021 06:40:17 GMT
• Title: Detecting Propaganda on the Sentence Level during the COVID-19 Pandemic
• Authors: Rong-Ching Chang, Chu-Hsing Lin
• Abstract summary: malicious cyber-enabled actions may cause increasing social polarization, health crises, and property loss. Using fine-tuned contextualized embedding trained on Reddit, we tackle the detection of the propaganda of such user accounts. Our result shows that the pro-China group appeared to be tweeting 35 to 115 times more than the neutral group.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The spread of misinformation, conspiracy, and questionable content and information manipulation by foreign adversaries on social media has surged along with the COVID-19 pandemic. Such malicious cyber-enabled actions may cause increasing social polarization, health crises, and property loss. In this paper, using fine-tuned contextualized embedding trained on Reddit, we tackle the detection of the propaganda of such user accounts and their targeted issues on Twitter during March 2020 when the COVID-19 epidemic became recognized as a pandemic. Our result shows that the pro-China group appeared to be tweeting 35 to 115 times more than the neutral group. At the same time, neutral groups were tweeting more positive-attitude content and voicing alarm for the COVID-19 situation. The pro-China group was also using more call-for-action words on political issues not necessarily China-related.

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