  Internet memes have become an increasingly pervasive form of contemporary
social communication that attracted a lot of research interest recently. In
this paper, we analyze the data of 129,326 memes collected from Reddit in the
middle of March, 2020, when the most serious coronavirus restrictions were
being introduced around the world. This article not only provides a looking
glass into the thoughts of Internet users during the COVID-19 pandemic but we
also perform a content-based predictive analysis of what makes a meme go viral.
Using machine learning methods, we also study what incremental predictive power
image related attributes have over textual attributes on meme popularity. We
find that the success of a meme can be predicted based on its content alone
moderately well, our best performing machine learning model predicts viral
memes with AUC=0.68. We also find that both image related and textual
attributes have significant incremental predictive power over each other.
