Style, Gender, and Genre

This chapter sums up which textual features beyond words were analysed and how they may play a role in readers’ evaluation of literary quality. It discusses sentence structures, parts of speech (PoS), bigrams, and cliché expressions. It describes how topic modelling was used to analyse thematic differences and how predictive modelling was applied to explore which textual and contextual features most influenced the ratings for literary quality. Mean sentence length, in number of words per sentence, proved to be a very good indicator. Next, Dutch Literary novels by women and men are compared in several computational ways and the influence of the author’s gender on readers’ perceptions is described in more detail. Finally, the feedback loop of genre is discussed.

Art · Bigram · Epistemology · Linguistics · Literature · Natural language processing · Perception · Quality (philosophy) · Sentence · Style (visual arts) · Writing style · Artificial Intelligence · Authorship Attribution and Profiling · Computational and Text Analysis Methods · Computer Science · Philosophy · Psychology · Topic Modeling