Abstract
While humor has been historically studied from a psychological, cognitive and linguistic standpoint, its study from a computational perspective is an area yet to be explored in Computational Linguistics. There exist some previous works, but a characterization of humor that allows its automatic recognition and generation is far from being specified. In this work we build a crowdsourced corpus of labeled tweets, annotated according to its humor value, letting the annotators subjectively decide which are humorous. A humor classifier for Spanish tweets is assembled based on supervised learning, reaching a precision of 84 % and a recall of 69 %.
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Notes
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Taken from https://twitter.com/chistetipico/status/430549009812291584. It has been slightly adapted to maintain an appropriate language.
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Perplexity is a measurement of how well a probability model predicts a sample. Low perplexity indicates the probability model is good at predicting the sample. It is defined as \(2^{- \frac{1}{n} \sum _{i=1}^n \log _2 p(x_i)}\), where \(x_1, \ldots , x_n\) are the sample data and \(p(x_i)\) is the probability assigned to each one.
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These tweets show traits of different variaties of the Spanish language among them. At least three countries were identified: Colombia, Spain and Uruguay.
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Note that Kappa assumes a fixed number of annotators. For this reason, we measure it with 2 and 6, in order to give an idea of the agreement having a value with many tweets but few annotators, and other value with few tweets but many annotators.
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The codebase for the classifier and the corpus built can be found in https://github.com/pln-fing-udelar/pghumor.
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Castro, S., Cubero, M., Garat, D., Moncecchi, G. (2016). Is This a Joke? Detecting Humor in Spanish Tweets. In: Montes y Gómez, M., Escalante, H., Segura, A., Murillo, J. (eds) Advances in Artificial Intelligence - IBERAMIA 2016. IBERAMIA 2016. Lecture Notes in Computer Science(), vol 10022. Springer, Cham. https://doi.org/10.1007/978-3-319-47955-2_12
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