Detecting Propaganda on the Sentence Level during the COVID-19 Pandemic
This addresses the problem of misinformation spread on social media during health crises, but it is incremental as it applies an existing method to new data.
The paper tackled detecting propaganda on Twitter during the COVID-19 pandemic by fine-tuning contextualized embeddings on Reddit data, finding that pro-China accounts tweeted 35 to 115 times more than neutral groups, which posted more positive content and expressed alarm about COVID-19.
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.