Abstract
Verbalization tasks contribute to a better understanding of consumers’ likes and willingness, which is a requirement in the field of sensory analysis. Lexicometry, also known as textual statistics, text mining, or textual data science, applies a multidimensional statistical approach highly capable of extracting information from free text descriptions of products. These verbalization tasks are particularly effective when used as a complement to holistic methods, such as sorting task or napping. We propose here an original methodology based on multiple-factor analysis for contingency tables (MFACT) that can function even when the judges use different languages. We present this methodology with data from a hall test session where the judges describe eight Catalan wines after performing a sorting task. Part of the panel uses Catalan and another part uses French. No translation is required to apply the method.
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Bécue-Bertaut, M., Álvarez-Esteban, R., Canals, JM. (2023). Use of Lexicometry in Sensometrics, an Essential Complement to Holistic Methods an Original Methodology. In: Gómez-Corona, C., Rodrigues, H. (eds) Consumer Research Methods in Food Science. Methods and Protocols in Food Science . Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3000-6_19
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