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Other literature type . Preprint . 2018
https://doi.org/10.48550/arxiv...
Article . 2018
License: arXiv Non-Exclusive Distribution
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Explorations in an English Poetry Corpus: A Neurocognitive Poetics Perspective

Authors: Jacobs, Arthur M.;

Explorations in an English Poetry Corpus: A Neurocognitive Poetics Perspective

Abstract

This paper describes a corpus of about 3000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction and non-fiction written by more than 130 authors (e.g., Darwin, Dickens, Shakespeare). Quantitative Narrative Analysis (QNA) is used to explore a cleaned subcorpus, the Gutenberg English Poetry Corpus (GEPC) which comprises over 100 poetic texts with around 2 million words from about 50 authors (e.g., Keats, Joyce, Wordsworth). Some exemplary QNA studies show author similarities based on latent semantic analysis, significant topics for each author or various text-analytic metrics for George Eliot's poem 'How Lisa Loved the King' and James Joyce's 'Chamber Music', concerning e.g. lexical diversity or sentiment analysis. The GEPC is particularly suited for research in Digital Humanities, Natural Language Processing or Neurocognitive Poetics, e.g. as training and test corpus, or for stimulus development and control.

Comment: 27 pages, 4 figures

Keywords

FOS: Computer and information sciences, Computer Science - Computation and Language, Computation and Language (cs.CL)

43 references, page 1 of 5

Aryani, A., Jacobs, A. M., & Conrad, M. (2013). Extracting salient sublexical units from written texts: “Emophon,” a corpus-based approach to phonological iconicity. Frontiers in Psychology, 4:654. doi: 10.3389/fpsyg.2013.00654

Aryani, A., Kraxenberger, M., Ullrich, S., Jacobs, A. M., & Conrad, M. (2016). Measuring the ba- sic a ective tone of poems via phonological saliency and iconicity. Psychology of Aesthetics, Creativity, and the Arts, 10, 191-204. DOI: 10.1037/ aca0000033

Bird, S., Klein, E., & Loper, E. (2009). Natural Language Processing with Python. O'Reilly Media, Inc.

Bornet C and Kaplan F (2017) A Simple Set of Rules for Characters and Place Recognition in French Novels. Front. Digit. Humanit. 4:6. doi: 10.3389/fdigh.2017.00006

Braun, M., Hutzler, F., Ziegler, J. C., Dambacher, M. & Jacobs, A. M. (2009). Pseudo homophone effects provide evidence of early lexico-phonological processing in visual word recognition. Human brain mapping, 30(7), 1977-1989. [OpenAIRE]

Clements, G. N. (1990). The role of sonority in core syllabification. In J. Kingston & M. E. Beckman (Eds.), Papers in laboratory phonology I. Between the grammar and physics of speech (pp. 283-333). Cambridge: CUP.

Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990). Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41, 391-407.

Frank, S. L. (2013). Uncertainty reduction as a measure of cognitive load in sentence comprehension. Topics in Cognitive Science, 5(3), 475-494. doi: 10.1111/tops.12025 [OpenAIRE]

Ganascia J-G (2015) The Logic of the Big Data Turn in Digital Literary Studies. Front. Digit. Humanit. 2:7. doi: 10.3389/fdigh.2015.00007

Jacobs, A. M. (2015a). Neurocognitive poetics: Methods and models for investigating the

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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