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"Learn the Facts About COVID-19": Analyzing the Use of Warning Labels on TikTok Videos

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Zannettou,  Savvas
Internet Architecture, MPI for Informatics, Max Planck Society;

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2201.07726.pdf
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Citation

Ling, C., Gummadi, K., & Zannettou, S. (2022). "Learn the Facts About COVID-19": Analyzing the Use of Warning Labels on TikTok Videos. Retrieved from https://arxiv.org/abs/2201.07726.


Cite as: https://hdl.handle.net/21.11116/0000-0009-F871-0
Abstract
During the COVID-19 pandemic, health-related misinformation and harmful



content shared online had a significant adverse effect on society. To mitigate



this adverse effect, mainstream social media platforms employed soft moderation



interventions (i.e., warning labels) on potentially harmful posts. Despite the



recent popularity of these moderation interventions, we lack empirical analyses



aiming to uncover how these warning labels are used in the wild, particularly



during challenging times like the COVID-19 pandemic. In this work, we analyze



the use of warning labels on TikTok, focusing on COVID-19 videos. First, we



construct a set of 26 COVID-19 related hashtags, then we collect 41K videos



that include those hashtags in their description. Second, we perform a



quantitative analysis on the entire dataset to understand the use of warning



labels on TikTok. Then, we perform an in-depth qualitative study, using



thematic analysis, on 222 COVID-19 related videos to assess the content and the



connection between the content and the warning labels. Our analysis shows that



TikTok broadly applies warning labels on TikTok videos, likely based on



hashtags included in the description. More worrying is the addition of COVID-19



warning labels on videos where their actual content is not related to COVID-19



(23% of the cases in a sample of 143 English videos that are not related to



COVID-19). Finally, our qualitative analysis on a sample of 222 videos shows



that 7.7% of the videos share misinformation/harmful content and do not include



warning labels, 37.3% share benign information and include warning labels, and



that 35% of the videos that share misinformation/harmful content (and need a



warning label) are made for fun. Our study demonstrates the need to develop



more accurate and precise soft moderation systems, especially on a platform



like TikTok that is extremely popular among people of younger age.