Behavioral Patterns beyond Posting Negative Reviews Online: An Empirical View

Negative reviews on e-commerce platforms are posted to express complaints about unsatisfactory experiences. However, the exact knowledge of how online consumers post negative still remains unknown. To obtain an in-depth understanding users platforms, a big-data-driven approach with text mining and sentiment analysis is employed detect various behavioral patterns. Specifically, using 1,450,000 from JD.com, largest B2C platform in China, posting patterns temporal, perceptional emotional perspectives comprehensively explored. A massive amount across four sectors recent 10 years split into five levels reveal group discrepancies at fine resolution. The circadian rhythms reviewing after making purchases found, suggesting stable habits consumption. Consumers lower more intensive feelings, especially product pricing customer service attitudes, while those upper demonstrate stronger momentum emotion. value higher-level thus unexpectedly highlighted because less emotionalization biased narration, longer-lasting characteristic these consumers’ responses also stresses need for attention sellers. Our results shed light implementing distinguished proactive strategies different buyer groups help mitigate impact due reviews.