The Love Equation

At the same workshop where I presented our paper about animacy detection, I presented joint work with Mike KestemontChristof Schöch and Antal van den Bosch on a computational model of romantic relationships in French classical drama.

We frame this task as a ranking problem in which, for a given character, we try to assign the highest rank to the character with whom (s)he is most likely to be romantically involved. As data we use a publicly available corpus of French 17th and 18th century plays ( which is well suited for this type of analysis because of the rich markup it provides (e.g. indications of characters speaking). You should definitely check out this collection. Its detailed annotations are pretty amazing!

We focus on distributional, so-called second-order features, which capture how speakers are contextually embedded in the texts. At a mean reciprocal rate (MRR) of 0.9 and [email protected] of 0.81, our results are encouraging, suggesting that this approach might be successfully extended to other forms of social interactions in literature, such as antagonism or social power relations.

Karsdorp, Folgert & Kestemont, Mike & Schöch, Christof & Van den Bosch, Antal (2015). ‘The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama’. In Mark A. Finlayson, Ben Miller, Antonio Lieto, and Remi Ronfard (ed.). Proceedings of the Workshop on Computational Models of Narrative (CMN’15), May 26-28, 2015, Atlanta, USA, pp. 98–107. (Full text)