Keywords
Innovación docente y Analytics (GIIDA), Asimov, Fundación, caracterización de personajes, análisis clúster, data mining, Asimov, Foundation, character analysis, cluster analysis, data mining
Caracterización en la trilogía Foundation: un estudio cuantitativo basado en el análisis cluster
Abstract
Este trabajo analiza la caracterización de los personajes en la trilogía Foundation de Asimov, pues una de las principales críticas respecto a su obra en general, y a esta saga en particular, es la escasa profundidad de los mismos, que les lleva a ser muy parecidos entre sí. A fin de determinar de un modo más objetivo la veracidad de esta crítica, se ha utilizado la técnica del análisis clúster, empleada habitualmente en big data, sobre un conjunto de veintiséis personajes de la trilogía, que previamente han sido evaluados según el modelo OCEAN, con los factores definidos en el test NEO-PI-R. La conclusión de este análisis cuantitativo es doble. Por una parte, se ha confirmado la validez de esta propuesta metodológica, al menos para el caso concreto analizado, pues los resultados son coherentes con lo recogido en estudios cualitativos previos. Por otra, hemos verificado que efectivamente la caracterización de los personajes, sin llegar al extremo del que en ocasiones se ha acusado a Asimov, no es tan minuciosa ni compleja como en el caso de otros autores.
This work analyses characterisation in Asimov s Foundation trilogy, as one of the main objections to his work in general and this series in particular is the shallowness of the characters, which makes them very similar to each other. To determine the veracity of such criticism in a more objective manner, we have used a Big Data technique cluster analysis, applied to a set of twenty-six characters in the trilogy, which have been previously evaluated according to the OCEAN model, with the factors defined in the NEO-PI-R test. The conclusion of this quantitative analysis is twofold. Firstly, the validity of this methodological proposal has been confirmed, at least for the specific case analysed, since the results are consistent with those of previous qualitative studies. Secondly, the characters, although not as shallow as often argued, have been shown to be somewhat lacking in roundness and development.
This work analyses characterisation in Asimov s Foundation trilogy, as one of the main objections to his work in general and this series in particular is the shallowness of the characters, which makes them very similar to each other. To determine the veracity of such criticism in a more objective manner, we have used a Big Data technique cluster analysis, applied to a set of twenty-six characters in the trilogy, which have been previously evaluated according to the OCEAN model, with the factors defined in the NEO-PI-R test. The conclusion of this quantitative analysis is twofold. Firstly, the validity of this methodological proposal has been confirmed, at least for the specific case analysed, since the results are consistent with those of previous qualitative studies. Secondly, the characters, although not as shallow as often argued, have been shown to be somewhat lacking in roundness and development.
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