Modeling "worth by association" in US book reviews, 1905–25.
This study builds on and responds to previous cultural analytics work on book reviews by comparing how terms related to genre, medium, and aesthetic judgment changed between 1905 and 1925 in a sample of book reviews published in the US periodicals. In the exploratory phase of this project, terms see...
| Publicado en: | Digital Scholarship in the Humanities Vol. 40; no. 1; pp. 170 - 189 |
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| Formato: | Artículo |
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Oxford University Press / USA
Apr2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=184296848&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 184296848 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: Apr2025 vid: 40 iid: 1 pid: 622 pub: Oxford University Press / USA artinfo: ui: 184296848 10.1093/llc/fqaf012 ppf: 170 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.8MB tig: atl: Modeling "worth by association" in US book reviews, 1905–25. aug: au: Lavin, Matthew J affil: Data Analytics Program, Denison University, 100 W College Street, OH 43023, United States su: Aesthetic judgment Calendars (Publications) Periodical publishing Data analytics Centroid sug: subj: Aesthetic judgment Calendars (Publications) Periodical publishing Data analytics Centroid keyword: book reviews linear regression periodicals reviews word movers distance ab: This study builds on and responds to previous cultural analytics work on book reviews by comparing how terms related to genre, medium, and aesthetic judgment changed between 1905 and 1925 in a sample of book reviews published in the US periodicals. In the exploratory phase of this project, terms seemingly related to categorization are identified and divided into "feature families." In the confirmatory phase, feature family terms are analyzed for their relatedness to one another and then evaluated for how well they predict book review dates. This comparison is conducted using a featurization method called Word Mover's Similarity Centroid Regression, which adapts the idea of Word Mover's Distance for a regression task. The medium feature family proved to be the most predictive of a review's publication date, followed by judgment terms, and then genre terms. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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