Year: 2024
Type: conference-paper
Abstract: Prior work has highlighted the importance of context in the identification of sarcasm by humans and language models.This work examines how much context is required for a better identification of sarcasm by both parties.We collect textual responses to dialogical prompts and sarcasm judgment to the responses placed after long contexts, short contexts, and no contexts.We find that both for humans and language models, the presence of context is generally important in identifying sarcasm in the response.But increasing the amount of context provides no added benefit to humans (long = short > none).This is the same for language models, but only on easily agreed-upon sentences; for sentences with disagreement among human evaluators, longer context provided more benefit than shorter context.Also, we show how, despite the low agreement in human evaluation, the sarcasm detection patterns by the manipulation of context amount stay consistent.
Authors: Hyewon Jang, Moritz Jakob, Diego Frassinelli
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4401042953