Visual Semantics of Memes: (Re)Interpreting Memetic Content and Form for Information Studies.

Here we attempt to contextualize memetics for Information Studies by reinterpreting Internet Memetics. In doing so, we propose a way to empirically study semantics of informational content. This is done by collecting images from meme entries on KnowYourMeme, a digital meme repository, and clustering features found in those images. The features are found using Google Cloud Vision, Google's computer vision project. We suggest how informational meaning (semantics) is shaped between similarity (operating as the idea of the meme) and difference (features in the image). Early results show that memetic ideas may be referenced as the shape of information across image collections. [ABSTRACT FROM AUTHOR]