2022
AAAI
AAAI 2022
Memotion Analysis through the Lens of Joint Embedding (Student Abstract)
Abstract
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.
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Interdisciplinary and Machine Learning and Natural Language Processing
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Hot Topic Early Bird
— image-text matching
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Core AI > Multimodal Learning
Machine Learning > Core Methods > Embedding Learning
Deep Learning > Architectures > Neural Networks
Interdisciplinary > Social > Social Media Analysis
Natural Language Processing > Applications > Sentiment Analysis
Machine Learning > Learning Types > Multi-Modal Learning
Deep Learning > Learning Types > Multi-Modal Learning