How Brand Authenticity and Consumer Brand Engagement Can Be Expressed in Reviews: A Text Mining Approach

Abstract

The current study aims to explore brand authenticity (and the related constructs: the need for uniqueness and brand love) and consumer brand engagement in consumers’ sentiments toward restaurants on online reviews. This research uses a text mining technique, applying sentiment analysis to the reviews. The data is retrieved from Yelp.com, and uses a randomly selected sample of 3,877 reviews of restaurants, from seven cities in the USA. This paper proposes a specific aggregated dictionary for brand authenticity, consumer brand engagement and related constructs, based on previously validated scales which contribute to perform a more multi-faceted analysis. The findings contribute to the marketing research by unfolding a high level of consumer-brand engagement and brand authenticity in online reviews, revealing that positive sentimental attachment toward a focal object in reviews is an essential source of information.