Text-based electronic word-of-mouth (eWOM) communication has increasingly become an important channel for consumers to exchange information about products and services. How to effectively utilize the enormous amount of text information poses a great challenge to marketing researchers and practitioners. This study takes an initial step to investigate the validities and usefulness of text mining, a promising approach in generating valuable information from eWOM communication. Bilateral data were collected from both eWOM senders and readers via two web-based surveys. Results provide initial evidence for the validity and utility of text mining and demonstrate that the linguistic indicators generated by text analysis are predictive of eWOM communicators’ attitudes toward a product or service. Text analysis indicators (e.g., Negations and Money) can explain additional variance in eWOM communicators’ attitudes above and beyond the star ratings and may become a promising supplement to the widely used star ratings as indicators of eWOM valence.
Author(s): Chuanyi Tang and Lin Guo
Organization(s): Old Dominion University and University of New Hampshire
Source: Marketing Letters