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Article published In: Empirical Studies of Literariness
Edited by Massimo Salgaro and Paul Sopčák
[Scientific Study of Literature 8:1] 2018
► pp. 165–208

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(Neuro-)Cognitive poetics and computational stylistics

 | Freie Universität Berlin
Published online: 17 January 2019
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https://doi.org/10.1075/ssol.18002.jac
Abstract
This perspective paper discusses four general desiderata of current computational stylistics and (neuro-)cognitive poetics concerning the development of (a) appropriate databases/training corpora, (b) advanced qualitative-quantitative narrative analysis (Q2NA) and machine learning tools for feature extraction, (c) ecologically valid literary test materials, and (d) open-access reader-response data banks. In six explorative computational stylistics studies, it introduces a number of tools that provide QNA indices of the foregrounding potential at the sublexical, lexical, inter- and supralexical levels for poems by Shakespeare, Blake, or Dickens. These concern lexical diversity and aesthetic potential, sentiment analysis, sublexical sonority scores or phrase structure, and topics analysis. The results illustrate the complex interplay of stylistic features and the necessity for theoretical guidance and interdisciplinary cooperation in selecting adequate training corpora, QNA tools, test texts, and response measures.
Article outline
  • Towards representative and reliable training corpora in several languages
  • The training corpus as a statistical reader model
  • QNA and machine learning tools for extracting and determining the importance of text features
  • Well selected, ecologically valid literary test materials and reliable open-access reader-response data banks
  • Illustrative studies merging (neuro-)cognitive poetics and computational stylistics
    • Study 1. Lexical distinctiveness
    • Study 2. Lexical diversity and concreteness
    • Study 3. Sentiment analysis and lexical aesthetic potential
    • Study 4. Affective sublexical indices: Tender vs. aggressive consonants and sonority score
    • Study 5. Interlexical indices: Bigram novelty, tenor vehicle similarity, and arousal span
    • Study 6. Supralexical indices (lines, sentences, stanzas, poem)
      • Lines
      • Sentences
      • Stanza dynamics
      • Topics
  • Discussion and outlook
  • Notes
  • References
References (144)
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Cited by (10)

Cited by ten other publications

Castano, Emanuele, Jessica Zanella, Fatemeh Saedi, Lisa Zunshine & Luca Ducceschi
2024. On the Complexity of Literary and Popular Fiction. Empirical Studies of the Arts 42:1 ► pp. 281 ff. DOI logo
Gracheva, Marianna
2022. Style of creative nonfiction. Scientific Study of Literature 12:1-2 ► pp. 49 ff. DOI logo
Jacobs, Arthur M. & Annette Kinder
2022. Computational Models of Readers' Apperceptive Mass. Frontiers in Artificial Intelligence 5 DOI logo
Nishihara, Takayuki
2022. EFL learners’ reading traits for lexically easy short poetry. Cogent Education 9:1 DOI logo
Papp-Zipernovszky, Orsolya, Anne Mangen, Arthur Jacobs & Jana Lüdtke
2022. Shakespeare sonnet reading: An empirical study of emotional responses. Language and Literature: International Journal of Stylistics 31:3 ► pp. 296 ff. DOI logo
Jacobs, Arthur M., Berenike Herrmann, Gerhard Lauer, Jana Lüdtke & Sascha Schroeder
2020. Sentiment Analysis of Children and Youth Literature: Is There a Pollyanna Effect?. Frontiers in Psychology 11 DOI logo
Usée, Franziska, Arthur M. Jacobs & Jana Lüdtke
2020. From Abstract Symbols to Emotional (In-)Sights: An Eye Tracking Study on the Effects of Emotional Vignettes and Pictures. Frontiers in Psychology 11 DOI logo
Xue, Shuwei, Arthur M. Jacobs & Jana Lüdtke
2020. What Is the Difference? Rereading Shakespeare’s Sonnets —An Eye Tracking Study. Frontiers in Psychology 11 DOI logo
Jacobs, Arthur M.
2019. Sentiment Analysis for Words and Fiction Characters From the Perspective of Computational (Neuro-)Poetics. Frontiers in Robotics and AI 6 DOI logo
[no author supplied]
2022. Poetic Metaphors [Figurative Thought and Language, 15], DOI logo

This list is based on CrossRef data as of 4 december 2025. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

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