Characterization in Foundation's trilogy: a quantitative study based on cluster analysis

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.