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Automatic Humour Detection

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If you have a question about this talk, please contact Diarmuid Ó Séaghdha.

At this session of the NLIP Reading Group we’ll be discussing two papers on computational humour:

Rada Michalcea and Carlo Strapparava. 2005. Making Computers Laugh: Investigations in Automatic Humor Recognition. In Proceedings of HLT -EMNLP-05.

Abstract: Humor is one of the most interesting and puzzling aspects of human behavior. Despite the attention it has received in fields such as philosophy, linguistics, and psychology, there have been only few attempts to create computational models for humor recognition or generation. In this paper, we bring empirical evidence that computational approaches can be successfully applied to the task of humor recognition. 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.

Clint Burfoot and Timothy Baldwin. Automatic Satire Detection: Are You Having a Laugh?. In Proceedings of ACL -09 (short paper).

Abstract: We introduce the novel task of determining whether a newswire article is “true” or satirical. We experiment with SVMs, feature scaling, and a number of lexical and semantic feature types, and achieve promising results over the task.

If you only have time to read one of these papers, Mihalcea and Strapparava (2005) is suggested.

This talk is part of the Natural Language Processing Reading Group series.

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