Visual Semantics of Memes: (Re)Interpreting Memetic Content and Form for Information Studies. Issue 1 (14th October 2022)

• Record Type: Journal Article
• Authors: Smith, Alexander O.; Tacheva, Jasmina; Hemsley, Jeff
• Is Part Of: Proceedings of the Association for Information Science and Technology. Volume 59:Issue 1(2022)
• Page Start: 800
• Page End: 802
• Publication Date: 2022-10-14
• Subjects: Computer Vision -- Memetics -- Network Clustering -- Semantic Information -- Visual Methods; Information science -- Congresses; Information technology -- Congresses; Information science; Information technology; Conference papers and proceedings; 020
• DOI: 10.1002/pra2.731
• Languages: English
• ISSNs: 2373-9231

Abstract

ABSTRACT: 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.