Work

Memotion Analysis through the Lens of Joint Embedding

Year: 2021

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2111.07074

Authors: Gunti, Nethra, Ramamoorthy, Sathyanarayanan, Patwa, Parth, Das, Amitava

Institutions: University of California, Los Angeles, Indian Institute of Information Technology Sri City, Wipro (India), University of South Carolina

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3213413232

Cites: 3

Cited by:

Related to: 10