Journal of Writing Research Feb 2016 OA PDF

Finding genre signals in academic writing

Ryan Omizo ; William Hart-Davidson

Abstract

This article proposes novel methods for computational rhetorical analysis to analyze the use of citations in a corpus of academic texts. Guided by rhetorical genre theory, our analysis converts texts to graph-theoretic graphs in an attempt to isolate and amplify the predicted patterns of recurring moves that are associated with stable genres of academic writing. We find that our computational method shows promise for reliably detecting and classifying citation moves similar to the results achieved by qualitative researchers coding by hand as done by Karatsolis (this issue). Further, using pairwise comparisons between advisor and advisee texts, valuable applications emerge for automated computational analysis as formative feedback in a mentoring situation.

Journal
Journal of Writing Research
Published
2016-02-01
DOI
10.17239/jowr-2016.07.03.08
CompPile
Open Access
OA PDF Diamond
Topics
rhetorical criticism genre theory qualitative research quantitative research digital rhetoric
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Citation Context

Cited by in this index (14)

  1. Yang et al. (2024)
    Pathological Liars: Algorithmic Knowing in the Rhetorical Ecosystem of Wallstreetbets
    Rhetoric Society Quarterly
  2. Omizo et al. (2024)
    Is Genre Enough? A Theory of Genre Signaling as Generative AI Rhetoric
    Rhetoric Society Quarterly
  3. Majdik et al. (2024)
    Rhetoric of/with AI: An Introduction
    Rhetoric Society Quarterly
  4. DeVasto (2024)
    Toward Rhetorically Infused Methods for Relational Network Modeling: The Visual…
    Technical Communication Quarterly
  5. Knowles (2024)
    Machine-in-the-loop writing: Optimizing the rhetorical load
    Computers and Composition
Show all 14 →
  1. Gallagher et al. (2023)
    Analyses of seven writing studies journals, 2000–2019, Part II: Data-driven ide…
    Computers and Composition
  2. Gallagher et al. (2023)
    Analyses of seven writing studies journals, 2000–2019, Part I: Statistical tren…
    Computers and Composition
  3. Graham et al. (2022)
    AI for Social Justice: New Methodological Horizons in Technical Communication
    Technical Communication Quarterly
  4. Zhu et al. (2021)
    A machine learning algorithm for sorting online comments via topic modeling
    Communication Design Quarterly
  5. Graham (2021)
    The Opioid Epidemic and the Pursuit of Moral Medicine: A Computational-Rhetoric…
    Written Communication
  6. Gallagher et al. (2020)
    Peering into the Internet Abyss: Using Big Data Audience Analysis to Understand…
    Technical Communication Quarterly
  7. Gray et al. (2020)
    Tracing Ecologies of Code Literacy and Constraint in Emojis as Multimodal Publi…
    Computers and Composition
  8. Lauer et al. (2018)
    Hand Collecting and Coding Versus Data-Driven Methods in Technical and Professi…
    IEEE Transactions on Professional Communication
  9. Laquintano et al. (2017)
    How Automated Writing Systems Affect the Circulation of Political Information Online
    Literacy in Composition Studies

References (0)

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