Alignment and Inconsistency between Textual Sentiment and Star Ratings in Online Product Reviews: A Reflexive Thematic Analysis - Sastika Seli; Yulfi Yulfi; Episiasi Episiasi (Universitas Pendidikan Mandalika, 2026)
Online product reviews combine numerical star ratings with written reviews to communicate consumer evaluations. While recent studies highlight frequent mismatches between textual sentiment and numerical ratings, few have examined this phenomenon qualitatively. This research investigates how linguistic sentiment aligns or diverges from star ratings to understand the pragmatic functions behind these inconsistencies. The research analyzes 120 anonymized furniture reviews collected from the IKEA Australia website. A two-stage methodology was applied: a descriptive overview classifying sentiment-rating consistency, followed by Reflexive Thematic Analysis (RTA) to examine linguistic richness and rating alignment. The analysis reveals four dominant evaluative patterns: Polite Dissatisfaction, Understated Positivity, Expressive Dissatisfaction, and Low-Information Reviews. Reviewers frequently employ politeness strategies, contrastive structures, and evaluative restraint, resulting in partial or complete mismatches between expressed sentiment and numerical scores. These results indicate that star ratings and written texts serve distinct communicative purposes and should be interpreted together rather than in isolation. The research contributes to qualitative sentiment analysis and digital pragmatics by demonstrating that sentiment-rating inconsistency is a deliberate pragmatic strategy rather than an analytical measurement error.