Blackcurrent, blueberry, pancetta, chestnut, spicey, crisp, complex, oxidized. What do all these words have in common? They were used by “civilians” and experts to describe wines in three regions of Australia and Bordeau, France. In their paper Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines, Lira Souza Gonzaga, Dimitra L. Capone, Susan E.P. Bastian, Lukas Danner and David W. Jeffery used WordStat to, “build a content analysis dictionary to help them evaluate whether content analysis based on wine sensory attributes could differentiate wines from different regions and generate a guide for sample selection of regional wines for this and future studies.” The paper also uses correspondence analysis and other features of WordStat to see how different comments from different groups of reviewers related to the selected wine regions.
In addition to its specific insights into the wine regions being studied, the paper illustrates how content analysis can be used in food science to evaluate and study sensory characteristics of different products as well as quality and other factors.
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