(2018) Reiter, Nils; Krautter, Benjamin; Pagel, Janis; Willand, Marcus
In this paper, we aim at identifying protagonists in plays automatically. To this end, we train a classifier using various features and investigate the importance of each feature. A challenging aspect here is that the number of spoken words for a character is a very strong baseline. We can show, however, that a) the stage presence of characters and b) topics used in their speech can help to detect protagonists even above the baseline.
In the paper we present a method for the analysis of entity associations that real readers make in their reviews on goodreads.com, a social reading platform - and first results and insights of our analysis.
