Understanding Visual Memes: An Empirical Analysis of Text Superimposed on Memes Shared on Twitter

Source: Yuhao Du, Muhammad Aamir Masood, Kenneth Joseph
Affiliation: Proceedings of the Fourteenth International AAAI Conference on Web and Social Media

This academic paper has the following abstract:

Visual memes have become an important mechanism through which ideologically potent and hateful content spreads on to- day’s social media platforms. At the same time, they are also a mechanism through which we convey much more mun- dane things, like pictures of cats with strange accents. Lit- tle is known, however, about the relative percentage of vi- sual memes shared by real people that fall into these, or other, thematic categories. The present work focuses on vi- sual memes that contain superimposed text. We carry out the first large-scale study on the themes contained in the text of these memes, which we refer to as image-with-text memes. We find that 30% of the image-with-text memes in our sam- ple which have identifiable themes are politically relevant, and that these politically relevant memes are shared more often by Democrats than Republicans. We also find dispari- ties in who expresses themselves via image-with-text memes, and images in general, versus other forms of expression on Twitter. The fact that some individuals use images with text to express themselves, instead of sending a plain text tweet, suggests potential consequences for the representativeness of analyses that ignore text contained in images.

Keywords: Computer Science , Memes , Tech Ethics