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  Topic model analysis of metaphor frequency for psycholinguistic stimuli

Bethard, S., Lai, V. T., & Martin, J. (2009). Topic model analysis of metaphor frequency for psycholinguistic stimuli. In Proceedings of the NAACL HLT Workshop on Computational Approaches to Linguistic Creativity, Boulder, Colorado, June 4, 2009 (pp. 9-16). Stroudsburg, PA: Association for Computational Linguistics.

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Bethard, Steven1, Author
Lai, Vicky T.1, Author           
Martin, James1, Author
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1Department of Linguistics University of Colorado, ou_102880              

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 Abstract: Psycholinguistic studies of metaphor processing must control their stimuli not just for word frequency but also for the frequency with which a term is used metaphorically. Thus, we consider the task of metaphor frequency estimation, which predicts how often target words will be used metaphorically. We develop metaphor classifiers which represent metaphorical domains through Latent Dirichlet Allocation, and apply these classifiers to the target words, aggregating their decisions to estimate the metaphorical frequencies. Training on only 400 sentences, our models are able to achieve 61.3 % accuracy on metaphor classification and 77.8 % accuracy on HIGH vs. LOW metaphorical frequency estimation.

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Language(s): eng - English
 Dates: 2009
 Publication Status: Issued
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Title: The North American Chapter of the Association for Computational Linguistics (NAACL), Workshop on Computational Approaches to Linguistic Creativity
Place of Event: Boulder, CO
Start-/End Date: 2009-06-04

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Title: Proceedings of the NAACL HLT Workshop on Computational Approaches to Linguistic Creativity, Boulder, Colorado, June 4, 2009
Source Genre: Proceedings
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Publ. Info: Stroudsburg, PA : Association for Computational Linguistics
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 9 - 16 Identifier: ISBN: 978-1-932432-36-7
URI: http://www.aclweb.org/anthology-new/W/W09/W09-2000.pdf