Using Games to Create Language Resources: Successes and Limitations of the Approach

John Chamberlain 1 Karën Fort 2, 3 Ugo Kruschwitz 1 Mathieu Lafourcade 4 Massimo Poesio 1
1 University of Essex
2 INIST - Institut de l'information scientifique et technique
3 LIPN - Laboratoire d'Informatique de Paris-Nord
4 TEXTE - Exploration et exploitation de données textuelles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : One of the more novel approaches to collaboratively creating language resources in recent years is to use online games to collect and validate data. The most significant challenges collaborative systems face are how to train users with the necessary expertise and how to encourage participation on a scale required to produce high quality data comparable with data produced by "traditional" experts. In this chapter we provide a brief overview of collaborative creation and the different approaches that have been used to create language resources, before analysing games used for this purpose. We discuss some key issues in using a gaming approach, including task design, player motivation and data quality, and compare the costs of each approach in terms of development, distribution and ongoing administration. In conclusion, we summarise the benefits and limitations of using a gaming approach to resource creation and suggest key considerations for evaluating its utility in different research scenarios.
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Chapitre d'ouvrage
Gurevych, Iryna and Kim, Jungi. Theory and Applications of Natural Language Processing, Springer, pp.42, 2013, 978-3-642-35084-9
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Contributeur : Mathieu Lafourcade <>
Soumis le : vendredi 7 juin 2013 - 09:33:11
Dernière modification le : jeudi 24 mai 2018 - 15:59:23
Document(s) archivé(s) le : mardi 4 avril 2017 - 18:02:54

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John Chamberlain, Karën Fort, Ugo Kruschwitz, Mathieu Lafourcade, Massimo Poesio. Using Games to Create Language Resources: Successes and Limitations of the Approach. Gurevych, Iryna and Kim, Jungi. Theory and Applications of Natural Language Processing, Springer, pp.42, 2013, 978-3-642-35084-9. 〈lirmm-00831442〉

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