A Report on the 2020 Sarcasm Detection Shared Task

Abstract

Detecting sarcasm and verbal irony is critical for understanding peoples actual sentiments and beliefs. Thus, the field of sarcasm analysis has become a popular research problem in natural language processing. As the community working on computational approaches for sarcasm detection is growing, it is imperative to conduct benchmarking studies to analyze the current state-of-the-art, facilitating progress in this area. We report on the shared task on sarcasm detection we conducted as a part of the 2nd Workshop on Figurative Language Processing (FigLang 2020) at ACL 2020.

Sarcasm Detection with External Entity Information

“…In other words, the meanings of sentences/utterances with sarcasm are the opposite of what writers/speakers said. Recognizing whether a sentence/utterance contains sarcastic meanings is essential to downstream applications for correctly understanding speakers' intended sentiments and beliefs [1]. In the last decade, sarcasm detection has attracted a considerable interest from computational linguistics researchers.…”