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

Alexander O. Smith, Jasmina Tacheva, Jeff Hemsley

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)800-802
Number of pages3
JournalProceedings of the Association for Information Science and Technology
Issue number1
StatePublished - 2022


  • Computer Vision
  • Memetics
  • Network Clustering
  • Semantic Information
  • Visual Methods

ASJC Scopus subject areas

  • General Computer Science
  • Library and Information Sciences


Dive into the research topics of 'Visual Semantics of Memes: (Re)Interpreting Memetic Content and Form for Information Studies'. Together they form a unique fingerprint.

Cite this