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Communications of the ACM
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Getting serious about the development of computational humor
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
IEEE Intelligent Systems
Applied Computational Humor and Prospects for Advertising
Proceedings of the 2006 conference on Rob Milne: A Tribute to a Pioneering AI Scientist, Entrepreneur and Mountaineer
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
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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.