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Clustering of influential wine bloggers using automated content analysis techniques
Beedie School of Business, Simon Fraser University, Vancouver, Canada.
Faculty of Business and Economics, Monash University, Melbourne, Australia.
University of Verona, Verona, Italy.
Luleå University of Technology, Department of Business Administration, Technology and Social Sciences, Business Administration and Industrial Engineering.ORCID iD: 0000-0002-6481-9846
2019 (English)In: Journal of Wine Research, ISSN 0957-1264, E-ISSN 1469-9672, Vol. 30, no 2, p. 157-165Article in journal (Refereed) Published
Abstract [en]

This 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.

Place, publisher, year, edition, pages
Taylor & Francis, 2019. Vol. 30, no 2, p. 157-165
Keywords [en]
Marketing, bloggers, content analysis, clustering
National Category
Business Administration
Research subject
Industrial Marketing
Identifiers
URN: urn:nbn:se:ltu:diva-74383DOI: 10.1080/09571264.2019.1580188Scopus ID: 2-s2.0-85067081359OAI: oai:DiVA.org:ltu-74383DiVA, id: diva2:1323102
Note

Validerad;2019;Nivå 1;2019-06-11 (johcin)

Available from: 2019-06-11 Created: 2019-06-11 Last updated: 2022-10-14Bibliographically approved

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Diba, Hoda

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