Acta Psychol (Amst). 2026 Jul 14;269:107402. doi: 10.1016/j.actpsy.2026.107402. Online ahead of print.
ABSTRACT
Despite the growing influence of user-generated content (UGC) on tourism decisions and well-being, little research has examined how UGC characteristics affect tourists’ subjective well-being (TSWB). This study integrates the Stimulus-Organism-Response (S-O-R) framework and the Elaboration Likelihood Model (ELM) to investigate how review text length, sentiment polarity, and reviewer identity influence TSWB, mediated by review usefulness and moderated by photo quantity. Analyzing 31,676 reviews from Ctrip combining a BERT-Attention-BiLSTM deep learning and regression model, we find that (1) text length and reviewer identity positively predict review usefulness, while sentiment polarity has a negative effect; (2) review usefulness mediates the relationship between UGC features and TSWB; (3) photo quantity amplifies the effects of text length and reviewer identity on usefulness, but not sentiment polarity, suggesting emotional cues depend more on text than visuals. This study clarifies the mechanism linking UGC to well-being and offers practical insights for platforms and tourists.
PMID:42447576 | DOI:10.1016/j.actpsy.2026.107402
