World Wide Web

Product (mathematics)

Process (computing)

Brand image

Operating system

The Internet

Computer science

Lexicon

Business

Natural language processing

Advertising

Psychology

Mathematics

Consumer behaviour

Data science

Geometry

Information retrieval

Finance

Sentiment analysis

Order (exchange)

Journal of Retailing and Consumer Services

The growth of the Internet has led to massive availability of online consumer reviews. So far, papers studying online reviews have mainly analysed how non-textual features, such as ratings and volume, influence different types of consumer behavior, such as information adoption decisions or product choices. However, little attention has been paid to examining the textual aspects of online reviews in order to study brand image and brand positioning. The text analysis of online reviews inevitably raises the concept of “text mining”; that is, the process of extracting useful and meaningful information from unstructured text. This research proposes an unified, structured and easy-to-implement procedure for the text analysis of online reviews with the ultimate goal of studying brand image and brand positioning. The text mining analysis is based on a lexicon-based approach, the Linguistic Inquiry and Word Count (Pennebaker et al., 2007), which provides the researcher with insights into emotional and psychological brand associations.

Mining the text of online consumer reviews to analyze brand image and brand positioning