English

Memotion Analysis through the Lens of Joint Embedding

Machine Learning 2021-12-06 v3 Artificial Intelligence Computation and Language Computer Vision and Pattern Recognition

Abstract

Joint embedding (JE) is a way to encode multi-modal data into a vector space where text remains as the grounding key and other modalities like image are to be anchored with such keys. Meme is typically an image with embedded text onto it. Although, memes are commonly used for fun, they could also be used to spread hate and fake information. That along with its growing ubiquity over several social platforms has caused automatic analysis of memes to become a widespread topic of research. In this paper, we report our initial experiments on Memotion Analysis problem through joint embeddings. Results are marginally yielding SOTA.

Keywords

Cite

@article{arxiv.2111.07074,
  title  = {Memotion Analysis through the Lens of Joint Embedding},
  author = {Nethra Gunti and Sathyanarayanan Ramamoorthy and Parth Patwa and Amitava Das},
  journal= {arXiv preprint arXiv:2111.07074},
  year   = {2021}
}

Comments

Accepted as Student Abstract at AAAI-22

R2 v1 2026-06-24T07:37:10.116Z