  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.
