Abstract
Humor is an aspect of human behavior considered essential for inter-personal communication. Despite this fact, research in human-computer interaction has almost completely neglected aspects concerned with the automatic recognition or generation of humor. In this paper, we investigate the problem of humor recognition, and bring empirical evidence that computational approaches can be successfully applied to this task. Through experiments performed on very large data sets, we show that automatic classification techniques can be effectively used to distinguish between humorous and non-humorous texts, with significant improvements observed over apriori known baselines.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Stock, O., Strapparava, C.: Getting serious about the development of computational humour. In: Proceedings of the 8th International Joint Conference on Artificial Intelligence (IJCAI 2003), Acapulco, Mexico (August 2003)
Binsted, K., Ritchie, G.: Computational rules for punning riddles. Humor 10(1) (1997)
Taylor, J., Mazlack, L.: Computationally recognizing wordplay in jokes. In: Proceedings of CogSci 2004, Chicago (August 2004)
Mihalcea, R., Strapparava, C.: Bootstrapping for fun: Web-based construction of large data sets for humor recognition. In: Proceedings of the Workshop on Negotiation, Behaviour and Language (FINEXIN 2005), Ottawa, Canada (2005)
Lewis, D., Yang, Y., Rose, T., Li, F.: RCV1: A new benchmark collection for text categorization research. The Journal of Machine Learning Research 5, 361–397 (2004)
Singh, P.: The public acquisition of commonsense knowledge. In: Proceedings of AAAI Spring Symposium: Acquiring (and Using) Linguistic (and World) Knowledge for Information Access, Palo Alto, CA (2002)
Attardo, S.: Linguistic Theory of Humor. Mouton de Gruyter, Berlin (1994)
Ruch, W.: Computers with a personality? lessons to be learned from studies of the psychology of humor. In: Proceedings of the The April Fools Day Workshop on Computational Humour (2002)
Bucaria, C.: Lexical and syntactic ambiguity as a source of humor. Humor 17(3) (2004)
Miller, G.: Wordnet: A lexical database. Communications of the ACM 38(11), 39–41 (1995)
McCallum, A., Nigam, K.: A comparison of event models for Naive Bayes text classification. In: Proceedings of AAAI 1998 Workshop on Learning for Text Categorization (1998)
Joachims, T.: Text categorization with Support Vector Machines: learning with many relevant features. In: Proceedings of the European Conference on Machine Learning (1998)
Daelemans, W., Zavrel, J., van der Sloot, K., van den Bosch, A.: Timbl: Tilburg memory based learner, version 4.0, reference guide. Technical report, University of Antwerp (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mihalcea, R., Strapparava, C. (2005). Laughter Abounds in the Mouths of Computers: Investigations in Automatic Humor Recognition. In: Maybury, M., Stock, O., Wahlster, W. (eds) Intelligent Technologies for Interactive Entertainment. INTETAIN 2005. Lecture Notes in Computer Science(), vol 3814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590323_9
Download citation
DOI: https://doi.org/10.1007/11590323_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30509-5
Online ISBN: 978-3-540-31651-0
eBook Packages: Computer ScienceComputer Science (R0)