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International Conference on Intelligent Text Processing and Computational Linguistics

CICLing 2014: Computational Linguistics and Intelligent Text Processing pp 441–453Cite as

Credible or Incredible? Dissecting Urban Legends

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8404))

Abstract

Urban legends are a genre of modern folklore, consisting of stories about rare and exceptional events, just plausible enough to be believed. In our view, while urban legends represent a form of “sticky” deceptive text, they are marked by a tension between the credible and incredible. They should be credible like a news article and incredible like a fairy tale. In particular we will focus on the idea that urban legends should mimic the details of news (who, where, when) to be credible, while they should be emotional and readable like a fairy tale to be catchy and memorable. Using NLP tools we will provide a quantitative analysis of these prototypical characteristics. We also lay out some machine learning experiments showing that it is possible to recognize an urban legend using just these simple features.

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Author information

Authors and Affiliations

  1. Trento-RISE, Via Sommarive 18, Trento, I-38123, Italy

    Marco Guerini

  2. FBK-Irst, Via Sommarive 18, Trento, I-38123, Italy

    Carlo Strapparava

Authors
  1. Marco Guerini
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  2. Carlo Strapparava
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Editor information

Editors and Affiliations

  1. Center for Computing Research, National Polytechnic Institute, Av. Juan Dios Bátiz, Col. Nueva Industrial Vallejo, 07738, Mexico D.F, Mexico

    Alexander Gelbukh

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Guerini, M., Strapparava, C. (2014). Credible or Incredible? Dissecting Urban Legends. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54903-8_37

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  • DOI: https://doi.org/10.1007/978-3-642-54903-8_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54902-1

  • Online ISBN: 978-3-642-54903-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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