The Effects of Linguistic Coordination on Perceived Quality of Consumer Reviews: A Dual Process Perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Online consumer reviews, as a major source of information and influence, are of great interest to marketing researchers and practitioners. This study investigates the effects of linguistic coordination on perceived review quality. Drawing on the elaboration likelihood model, the authors theorize that two types of linguistic coordination—topic matching (semantic component) and language style matching (lexical component)—have profound effects on perceived review quality. Utilizing natural language processing tools and a novel clustering technique to measure matching, empirical analyses based on an IMDb data set support the positive direct effects of both types of matching. Moreover, the authors find that there is a negative interaction between topic matching and language style matching in affecting perceived review quality. The findings contribute to the understanding of online review quality, and the application of natural language processing enriches the methodological tool kit available to researchers.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.299 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it