Roles of negative emotions in customers’ perceived helpfulness of hotel reviews on a user-generated review website: A text mining approach

This paper aims to explore how emotional expressions embedded in online hotel reviews influence consumers’ helpfulness perceptions. In particular, this study develops and tests hypotheses analyzing empirical data with a text-mining method in the context of hotels to investigate how review valence influences the perceived helpfulness of online hotel reviews and to examine the role of negative emotional expressions embedded in online consumer reviews with respect to perceived helpfulness.

This study collected 520,668 online reviews involving 488 hotels in New York City (NYC) on Tripadvisor.com. Of these reviews, 69,202 reviews (13.29 per cent) that had received helpfulness votes were analyzed by a text mining method and negative binomial regression.

This study demonstrates that negative reviews are considered more helpful than positive reviews when potential customers read online hotel reviews for their future stay. However, when intensively negative emotions were expressed, the degree of helpfulness regarding negative reviews was diminished.

While emotional expressions prevail in online consumer reviews, surprisingly little attention has been devoted to the consequences of emotional expressions in consumers’ information processing and decision-making. Due to the nature of service, given the inseparability of production and consumption, which often hinders the execution of flawless service, consumers tend to be more dependent on reviews to minimize any potential failures they may encounter later on. Therefore, this study fills a gap by demonstrating that negative reviews and emotional expressions play a more crucial role in consumers’ information processing and decision-making.