Bayesian Analysis of the Heterogeneity of Literary Style

• MARTI FONT ^[1] ; XAVIER PUIG ^[1] ; JOSEP GINEBRA ^[1]
  1. [1] Universitat Politècnica de Catalunya

     Universitat Politècnica de Catalunya

     Barcelona, España

     
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 39, Nº. 2, 2016, págs. 205-227
• Idioma: inglés
• DOI: 10.15446/rce.v39n2.50151
• Títulos paralelos:
  • Análisis bayesiano de la heterogeneidad del estilo literario
• Enlaces
  • Texto completo
• Resumen
  • español

    Se propone un análisis estadístico para modelar la heterogeneidad del estilo literario en un conjunto de textos, para ello se utilizan simultáneamente diferentes características estilométricas, como longitud de palabra y la frecuencia de palabras función. Los datos consisten en varias tablas con el mismo número de filas, donde la fila i-ésima corresponde al texto i-ésimo. El análisis propuesto agrupa las filas de todas estas tablas simultáneamente en grupos de estilo homogéneo, en base a una mezcla finita de modelos multinomiales. El modelo propuesto tiene la ventaja sobre los análisis de conglomerados heurísticos habituales, de incorporar de forma natural el tamaño del texto, la naturaleza discreta de los datos y la dependencia entre las categorías. El modelo se selecciona y válida con la ayuda de simulaciones de la distribución predictiva a posteriori, junto con el uso de las expresiones en forma cerrada para la probabilidad a posteriori de cada uno de los modelos de mezcla considerados. Todo ello se ilustra a través de un análisis de la heterogeneidad en las obras de Shakespeare, y revisitando el problema de atribución de autoría del texto Tirant lo Blanc.

  • English

    We proposed statistical analysis of the heterogeneity of literary style in a set of texts that simultaneously use different stylometric characteristics, like word length and the frequency of function words. The data set consists of several tables with the same number of rows, with the i-th row of all tables corresponding to the i-th text. The analysis proposed clusters the rows of all these tables simultaneously into groups with homogeneous style, based on a finite mixture of sets of multinomial models, one set for each table. Different from the usual heuristic cluster analysis approaches, our method naturally incorporates the text size, the discrete nature of the data, and the dependence between categories in the analysis. The model is checked and chosen with the help of posterior predictive checks, together with the use of closed form expressions for the posterior probabilities that each of the models considered to be appropriate. This is illustrated through an analysis of the heterogeneity in Shakespeares plays, and by revisiting the authorship-attribution problem of Tirant lo Blanc.

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