This paper presents a new corpus for the Italian language representative of the fan-fiction genre. It comprises about 55k user-generated stories inspired to the original fantasy saga "Harry Potter" and published on a popular website. The corpus is large enough to support data-driven investigations in many directions, from more traditional studies on language variation aimed at characterizing this genre with respect to more traditional ones, to emerging topics in computational social science such as the identification of factors involved in the success of a story. The latter is the focus of the presented case-study, in which a wide set of multi-level linguistic features has been automatically extracted from a subset of the corpus and analysed in order to detect the ones which significantly discriminate successful from unsuccessful stories
The Style of a Successful Story: a Computational Study on the Fanfiction Genre
Dominique Brunato;Felice Dell'Orletta
2020
Abstract
This paper presents a new corpus for the Italian language representative of the fan-fiction genre. It comprises about 55k user-generated stories inspired to the original fantasy saga "Harry Potter" and published on a popular website. The corpus is large enough to support data-driven investigations in many directions, from more traditional studies on language variation aimed at characterizing this genre with respect to more traditional ones, to emerging topics in computational social science such as the identification of factors involved in the success of a story. The latter is the focus of the presented case-study, in which a wide set of multi-level linguistic features has been automatically extracted from a subset of the corpus and analysed in order to detect the ones which significantly discriminate successful from unsuccessful storiesI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
