2021 AAAI AAAI 2021

An Attention Based Multi-view Model for Sarcasm Cause Detection (Student Abstract)

Abstract

Abstract Sarcasm often relates to people’s implicit discontent with certain products and policies. Existing research mainly focus on sarcasm detection, while the deep causal relationships in the full conversation remained unexplored. This paper formulates a novel research question of sarcasm cause detection, and proposes an attention based model that simultaneously captures different semantic associations as well as the inner causal logics in multi-view manner. Experiments on public Reddit dataset prove the efficacy of the proposed model.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Knowledge & Reasoning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — sarcasm cause detection
🐣 Hot Topic Early Bird — causal reasoning
🐝 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