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Short videos have become one of the leading media used by younger generationsto express themselves online and thus a driving force in shaping onlineculture. In this context, TikTok has emerged as a platform where viral videosare often posted first. In this paper, we study what elements of short videosposted on TikTok contribute to their virality. We apply a mixed-method approachto develop a codebook and identify important virality features. We do sovis-\`a-vis three research hypotheses; namely, that: 1) the video content, 2)TikTok's recommendation algorithm, and 3) the popularity of the video creatorcontribute to virality.  We collect and label a dataset of 400 TikTok videos and train classifiers tohelp us identify the features that influence virality the most. While thenumber of followers is the most powerful predictor, close-up and medium-shotscales also play an essential role. So does the lifespan of the video, thepresence of text, and the point of view. Our research highlights thecharacteristics that distinguish viral from non-viral TikTok videos, laying thegroundwork for developing additional approaches to create more engaging onlinecontent and proactively identify possibly risky content that is likely to reacha large audience.

Slapping Cats, Bopping Heads, and Oreo Shakes: Understanding Indicators of Virality in TikTok Short Videos