Memotion Analysis through the Lens of Joint Embedding (Student Abstract)


  • Nethra Gunti IIIT Sri City, India
  • Sathyanarayanan Ramamoorthy IIIT Sri City, India
  • Parth Patwa UCLA, USA
  • Amitava Das Wipro AI lab, India AI Institute, University of South Carolina, USA



Joint Embedding, Multi-Modal Models, Vision And Language, Memotion Analysis


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.




How to Cite

Gunti, N., Ramamoorthy, S., Patwa, P., & Das, A. (2022). Memotion Analysis through the Lens of Joint Embedding (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12959-12960.