A quantitative, computational investigation of Computers and Composition: Using topic modeling over time to reveal patterns in textual data.
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| Title: | A quantitative, computational investigation of Computers and Composition: Using topic modeling over time to reveal patterns in textual data. |
|---|---|
| Authors: | Deets, Stuart1 (AUTHOR) deets008@umn.edu |
| Source: | Computers & Composition. Jun2026, Vol. 80, pN.PAG-N.PAG. 1p. |
| Subjects: | Artificial intelligence, Word processing software, Digital inclusion, Scholarly periodicals, Content analysis, Text mining, Authorship |
| Abstract: | • Using a distant reading, the approach reveals trends over 40 years. • Trends include decline of word processing and rise of artificial intelligence. • Journal's consistency of approach to technology: critical reflection. This computational study examines 1607 articles published in Computers and Composition from 1983 through 2025, using Structural Topic Modeling to analyze the journal's 40-year intellectual trajectory. Employing STM with temporal covariates, I identified 20 distinct topics and tracked their evolution across four decades of scholarship. The analysis reveals how the field has continuously negotiated relationships between technology and writing through recurring themes: automation anxieties, digital equity and access, and questions of authorship and originality. While technological platforms have shifted dramatically—from word processing to hypertext to social media to generative AI—the fundamental concerns remain consistent. Topics such as word processing, once dominant in the 1980s, have declined to near invisibility as these technologies became ubiquitous, while newer topics like artificial intelligence show unprecedented rapid growth. The field's response patterns demonstrate neither uncritical adoption nor reflexive resistance, but rather sustained critical engagement that interrogates technological change while remaining attentive to writing's human dimensions. This distant reading approach surfaces both dominant trends and marginalized areas of inquiry, revealing how Computers and Composition has developed sophisticated frameworks for understanding technology's role in writing—frameworks that remain essential as the field navigates an increasingly computational future. [ABSTRACT FROM AUTHOR] |
| Copyright of Computers & Composition is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 194397678 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A quantitative, computational investigation of Computers and Composition: Using topic modeling over time to reveal patterns in textual data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Deets%2C+Stuart%22">Deets, Stuart</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> deets008@umn.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computers+%26+Composition%22">Computers & Composition</searchLink>. Jun2026, Vol. 80, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Word+processing+software%22">Word processing software</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+inclusion%22">Digital inclusion</searchLink><br /><searchLink fieldCode="DE" term="%22Scholarly+periodicals%22">Scholarly periodicals</searchLink><br /><searchLink fieldCode="DE" term="%22Content+analysis%22">Content analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Text+mining%22">Text mining</searchLink><br /><searchLink fieldCode="DE" term="%22Authorship%22">Authorship</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: • Using a distant reading, the approach reveals trends over 40 years. • Trends include decline of word processing and rise of artificial intelligence. • Journal's consistency of approach to technology: critical reflection. This computational study examines 1607 articles published in Computers and Composition from 1983 through 2025, using Structural Topic Modeling to analyze the journal's 40-year intellectual trajectory. Employing STM with temporal covariates, I identified 20 distinct topics and tracked their evolution across four decades of scholarship. The analysis reveals how the field has continuously negotiated relationships between technology and writing through recurring themes: automation anxieties, digital equity and access, and questions of authorship and originality. While technological platforms have shifted dramatically—from word processing to hypertext to social media to generative AI—the fundamental concerns remain consistent. Topics such as word processing, once dominant in the 1980s, have declined to near invisibility as these technologies became ubiquitous, while newer topics like artificial intelligence show unprecedented rapid growth. The field's response patterns demonstrate neither uncritical adoption nor reflexive resistance, but rather sustained critical engagement that interrogates technological change while remaining attentive to writing's human dimensions. This distant reading approach surfaces both dominant trends and marginalized areas of inquiry, revealing how Computers and Composition has developed sophisticated frameworks for understanding technology's role in writing—frameworks that remain essential as the field navigates an increasingly computational future. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computers & Composition is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=194397678 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.compcom.2026.102998 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Word processing software Type: general – SubjectFull: Digital inclusion Type: general – SubjectFull: Scholarly periodicals Type: general – SubjectFull: Content analysis Type: general – SubjectFull: Text mining Type: general – SubjectFull: Authorship Type: general Titles: – TitleFull: A quantitative, computational investigation of Computers and Composition: Using topic modeling over time to reveal patterns in textual data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Deets, Stuart IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 87554615 Numbering: – Type: volume Value: 80 Titles: – TitleFull: Computers & Composition Type: main |
| ResultId | 1 |
