Computational analysis to explore authors' depiction of characters

This study involves automatically identifying the sociolinguistic characteristics of fictional characters in plays by analyzing their written “speech”. We discuss three binary classification problems: predicting the characters’ gender (male vs. female), age (young vs. old), and socioeconomic standing (upper-middle class vs. lower class). The text corpus used is an annotated collection of August Strindberg and Henrik Ibsen plays, translated into English, which are in the public domain. These playwrights were chosen for their known attention to relevant socioeconomic issues in their work. Linguistic and textual cues are extracted from the characters’ lines (turns) for modeling purposes. We report on the dataset as well as the performance and important features when predicting each of the sociolinguistic characteristics, comparing intraand inter-author testing.