Documents

  • paper4-2

    Final published version, 495 KB, PDF-document

DOI

We report on building a computational model of romantic relationships in a corpus of historical literary texts. 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 (http://www.theatre-classique.fr/) which is well suited for this type of analysis because of the rich markup it provides (e.g. indications of characters speaking). 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 MRR@1 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.
Original languageEnglish
Title of book/volumeProceedings of the Workshop on Computational Models of Narrative (CMN’15)
EditorsMark Finlayson, Ben Miller, Antonio Lieto, Remi Ronfard
Place of PublicationAtlanta, U.S.A
PublisherOASICS Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl Publishing, Germany
Pages98–107
Number of pages9
DOI
Publication statusPublished - May 2015

Publication series

NameOpenAccess Series in Informatics
PublisherOASICS Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl Publishing, Germany

    Research areas

  • French drama, social relations, social network, neural network, representation learning

ID: 1057317