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Documents authored by Karsdorp, Folgert

Document
DOI: 10.4230/OASIcs.CMN.2015.82
Animacy Detection in Stories

Authors: Folgert Karsdorp, Marten van der Meulen, Theo Meder, and Antal van den Bosch

Published in: OASIcs, Volume 45, 6th Workshop on Computational Models of Narrative (CMN 2015)

Abstract
This paper presents a linguistically uninformed computational model for animacy classification. The model makes use of word n-grams in combination with lower dimensional word embedding representations that are learned from a web-scale corpus. We compare the model to a number of linguistically informed models that use features such as dependency tags and show competitive results. We apply our animacy classifier to a large collection of Dutch folktales to obtain a list of all characters in the stories. We then draw a semantic map of all automatically extracted characters which provides a unique entrance point to the collection.
Cite as

Folgert Karsdorp, Marten van der Meulen, Theo Meder, and Antal van den Bosch. Animacy Detection in Stories. In 6th Workshop on Computational Models of Narrative (CMN 2015). Open Access Series in Informatics (OASIcs), Volume 45, pp. 82-97, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{karsdorp_et_al:OASIcs.CMN.2015.82,
  author =	{Karsdorp, Folgert and van der Meulen, Marten and Meder, Theo and van den Bosch, Antal},
  title =	{{Animacy Detection in Stories}},
  booktitle =	{6th Workshop on Computational Models of Narrative (CMN 2015)},
  pages =	{82--97},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-93-4},
  ISSN =	{2190-6807},
  year =	{2015},
  volume =	{45},
  editor =	{Finlayson, Mark A. and Miller, Ben and Lieto, Antonio and Ronfard, Remi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2015.82},
  URN =		{urn:nbn:de:0030-drops-52841},
  doi =		{10.4230/OASIcs.CMN.2015.82},
  annote =	{Keywords: animacy detection, word embeddings, folktales}
}
Document
DOI: 10.4230/OASIcs.CMN.2015.98
The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama

Authors: Folgert Karsdorp, Mike Kestemont, Christof Schöch, and Antal van den Bosch

Published in: OASIcs, Volume 45, 6th Workshop on Computational Models of Narrative (CMN 2015)

Abstract
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.
Cite as

Folgert Karsdorp, Mike Kestemont, Christof Schöch, and Antal van den Bosch. The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama. In 6th Workshop on Computational Models of Narrative (CMN 2015). Open Access Series in Informatics (OASIcs), Volume 45, pp. 98-107, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

Copy BibTex To Clipboard

@InProceedings{karsdorp_et_al:OASIcs.CMN.2015.98,
  author =	{Karsdorp, Folgert and Kestemont, Mike and Sch\"{o}ch, Christof and van den Bosch, Antal},
  title =	{{The Love Equation: Computational Modeling of Romantic Relationships in French Classical Drama}},
  booktitle =	{6th Workshop on Computational Models of Narrative (CMN 2015)},
  pages =	{98--107},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-93-4},
  ISSN =	{2190-6807},
  year =	{2015},
  volume =	{45},
  editor =	{Finlayson, Mark A. and Miller, Ben and Lieto, Antonio and Ronfard, Remi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.CMN.2015.98},
  URN =		{urn:nbn:de:0030-drops-52838},
  doi =		{10.4230/OASIcs.CMN.2015.98},
  annote =	{Keywords: French drama, social relations, neural network, representation learning}
}
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