The language of humour

Humour is one of the most interesting and puzzling aspects of human behaviour. Despite the attention it has received from fields such as philosophy, linguistics, and psychology, there have been only few attempts to create computational models for humour recognition and analysis. In this thesis, I u...

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Bibliographic Details
Main Author: Mihalcea, R
Other Authors: Pulman, S
Format: Thesis
Language:English
Published: 2010
Subjects:
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author Mihalcea, R
author2 Pulman, S
author_facet Pulman, S
Mihalcea, R
author_sort Mihalcea, R
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description Humour is one of the most interesting and puzzling aspects of human behaviour. Despite the attention it has received from fields such as philosophy, linguistics, and psychology, there have been only few attempts to create computational models for humour recognition and analysis. In this thesis, I use corpus-based approaches to formulate and test hypotheses concerned with the processing of verbal humour. The thesis makes two important contributions. First, it brings empirical evidence that computational approaches can be successfully applied to the task of humour recognition. Through experiments performed on very large data sets, I show that automatic classification techniques can be effectively used to distinguish between humorous and non-humorous texts, using content-based features or models of incongruity. Moreover, using a method for measuring feature saliency, I identify and validate several dominant word classes that can be used to characterize humorous text. Second, the thesis provides corpus-based support toward the validity of previously formulated linguistic theories, indicating that humour is primarily due to incongruity and humour-specific language. Experiments performed on collections of verbal humour show that both incongruity and content-based features can be successfully used to model humour, and that these features are even more effective when used in tandem.
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spelling oxford-uuid:a1cc3d1e-cc83-44dd-a2dd-6910fde3d2522022-03-27T02:15:41ZThe language of humourThesishttp://purl.org/coar/resource_type/c_db06uuid:a1cc3d1e-cc83-44dd-a2dd-6910fde3d252LinguisticsHumour ResearchComputational LinguisticsNatural Language ProcessingEnglishOxford University Research Archive - Valet2010Mihalcea, RPulman, SHumour is one of the most interesting and puzzling aspects of human behaviour. Despite the attention it has received from fields such as philosophy, linguistics, and psychology, there have been only few attempts to create computational models for humour recognition and analysis. In this thesis, I use corpus-based approaches to formulate and test hypotheses concerned with the processing of verbal humour. The thesis makes two important contributions. First, it brings empirical evidence that computational approaches can be successfully applied to the task of humour recognition. Through experiments performed on very large data sets, I show that automatic classification techniques can be effectively used to distinguish between humorous and non-humorous texts, using content-based features or models of incongruity. Moreover, using a method for measuring feature saliency, I identify and validate several dominant word classes that can be used to characterize humorous text. Second, the thesis provides corpus-based support toward the validity of previously formulated linguistic theories, indicating that humour is primarily due to incongruity and humour-specific language. Experiments performed on collections of verbal humour show that both incongruity and content-based features can be successfully used to model humour, and that these features are even more effective when used in tandem.
spellingShingle Linguistics
Humour Research
Computational Linguistics
Natural Language Processing
Mihalcea, R
The language of humour
title The language of humour
title_full The language of humour
title_fullStr The language of humour
title_full_unstemmed The language of humour
title_short The language of humour
title_sort language of humour
topic Linguistics
Humour Research
Computational Linguistics
Natural Language Processing
work_keys_str_mv AT mihalcear thelanguageofhumour
AT mihalcear languageofhumour