Relevance: communication and cognition
Relevance: communication and cognition
Clues for detecting irony in user-generated contents: oh...!! it's "so easy" ;-)
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
Semi-supervised recognition of sarcastic sentences in Twitter and Amazon
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Mining subjective knowledge from customer reviews: a specific case of irony detection
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
From humor recognition to irony detection: The figurative language of social media
Data & Knowledge Engineering
Making objective decisions from subjective data: Detecting irony in customer reviews
Decision Support Systems
A multidimensional approach for detecting irony in Twitter
Language Resources and Evaluation
| Hi-index | 0.00 |
This paper presents a unified theory of verbal irony for developing a computational model of irony. The theory claims that an ironic utterance implicitly communicates the fact that its utterance situation is surrounded by ironic environment which has three properties, but hearers can assume an utterance to be ironic even when they recognize that it implicitly communicates only two of the three properties. Implicit communication of three properties is accomplished in such a way that an utterance alludes to the speaker's expectation, violates pragmatic principles, and implies the speaker's emotional attitude. This paper also describes a method for computationally formalizing ironic environment and its implicit communication using situation theory with action theory.