Computer Vision and Internet Meme Genealogy: An Evaluation of Image Feature Matching as a Technique for Pattern Detection

Internet memes are a fundamental aspect of digital culture. Despite being individual expressions, they vastly transcend the level as windows into and vehicles for wide-stretching social, cultural, political narratives. Empirical research meme culture is thriving, yet particularly compartmentalized. In humanities social sciences, most efforts involve in-depth linguistic visual analyses mostly handpicked examples memes, begging question on origins meanings those particular expressions. technical disciplines, such computer science, focused large-scale identification classification images, well patterns “viral” spread at scale. This contribution aims to bridge chasm between depth scale by introducing three-step approach suitable “computational grounded theoretical” studies in which (1) an automated procedure establishes formal links images drawn from corpus paving way (2) network analysis infer relatedness spread, (3) practically classifying visually related file folders purpose further local, hermeneutic analysis. The demonstrated evaluated two datasets: artificially constructed, structured dataset naturally harvested unstructured dataset. Future horizons domains application discussed.