Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops

While humor is often thought to be beyond the reach of Natural Language Processing, we show that several aspects of single-word humor correlate with simple linear directions in Word Embeddings. In particular: (a) the word vectors capture multiple aspects discussed in humor theories from various disc...

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Bibliographic Details
Published inarXiv.org
Main Authors Gultchin, Limor, Patterson, Genevieve, Baym, Nancy, Swinger, Nathaniel, Kalai, Adam Tauman
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 24.05.2019
Subjects
Annotations
Clustering
Demographics
Natural language processing
Ratings
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Summary:While humor is often thought to be beyond the reach of Natural Language Processing, we show that several aspects of single-word humor correlate with simple linear directions in Word Embeddings. In particular: (a) the word vectors capture multiple aspects discussed in humor theories from various disciplines; (b) each individual's sense of humor can be represented by a vector, which can predict differences in people's senses of humor on new, unrated, words; and (c) upon clustering humor ratings of multiple demographic groups, different humor preferences emerge across the different groups. Humor ratings are taken from the work of Engelthaler and Hills (2017) as well as from an original crowdsourcing study of 120,000 words. Our dataset further includes annotations for the theoretically-motivated humor features we identify.
ISSN:2331-8422