MétaCan
Menu
Back to cohort
Record W3082192086 · doi:10.1163/26660393-bja10008

Generic Structure and Rhetorical Relations of Online Book Reviews in English, Japanese and Chinese

2020· article· en· W3082192086 on OpenAlexaff
Sonya Chik, Maite Taboada

Bibliographic record

VenueContrastive Pragmatics · 2020
Typearticle
Languageen
FieldComputer Science
TopicSentiment Analysis and Opinion Mining
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRhetorical questionLinguisticsCoherence (philosophical gambling strategy)Genre analysisComputer scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract We examine the generic structure and rhetorical relations that characterise online book reviews in English, Japanese and Chinese to describe the pragmatic features of this emerging genre in a contrastive light. The corpus we analyse contains online book reviews written by consumers for consumers. The purpose of the study is two-fold. First, we seek to identify the generic structure of online book reviews. Second, we investigate the cross-cultural variation in the rhetorical organisation of opinions and evaluations in written reviews across language communities. The reviews are analysed in terms of the generic stages of book reviews, which are determined by their overall communicative goals (Motta-Roth, 1995; Taboada, 2011). The stages are then mapped against rhetorical relations that capture the coherence and meaningful organisation of the text (Mann and Thompson, 1988). Results show that online book reviews in all three languages share a common generic structure comprising three broad stages: Metapragmatic Comment, Evaluation (Book Overall, Author, Plot, Character) and Recommendation. While Evaluation is the only obligatory stage, Metapragmatic Comment serves to prepare the reader for the Evaluation that follows. The recommendation stage is common in both English and Chinese reviews but is conspicuously absent in their Japanese counterpart. In terms of rhetorical patterns, Contrast, Concession and Antithesis relations are preferred in Metapragmatic Comment and Evaluation, while Motivation is typically present in the recommendation stage. This paper proposes a methodology for the contrastive analyses of pragmatic phenomena, illustrating this methodology through the study of an emerging online genre.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.853
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.273
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueContrastive PragmaticsSame topicSentiment Analysis and Opinion MiningFrench-language works237,207