Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops

Why is humor so difficult for machine learning and AI systems to understand? In light of recent studies in Psychology showing that individual words can be humorous Engelthaler & Hills (2017); Westbury et al. (2016), and in light of the fact that Word Embeddings (WEs) have been to shown to capture numerous properties of words (e.g., Mikolov et al., 2013), it is natural to study if and how WEs capture humor. First, we find that individual-word humor possesses many aspects of humor that have been discussed in general theories of humor, and that many of these aspects of humor are captured by WEs. To more deeply understand which features of humor WEs capture and to what extent, we draw on existing theories of humor to define a number of candidate features of word humor. Interestingly, many of these theories can be applied to word humor.