Clustering of influential wine bloggers using automated content analysis techniques

Abstract

ABSTRACTThis paper considers a sample of successful wine bloggers, and clusters them into four distinct segments that could be targeted by wine marketers in different ways. Using text that they wrote in response to being named to a survey of 100 top wine blogs, we employ an advanced textual analysis tool (LIWC) to categorize the writings according to the following characteristics: analytical thinking, clout, authenticity, and emotional tone. This data is then used in a clustering procedure that distinguishes four distinct groups of bloggers: the Analysts, the Agnostics, the Authentic Pessimists, and the Confident Optimists.