Comparison of free-comment online product reviews and central location product testing for sensory product characterisation: A case study with coffee consumers
Josafath I. Espinosa-Ramos , Scott C. Hutchings , Yash Dixit , David Jin , Grace S. Ryan , Mieke Marsden , Sara R. Jaeger , Marlon M. Reis
{"title":"Comparison of free-comment online product reviews and central location product testing for sensory product characterisation: A case study with coffee consumers","authors":"Josafath I. Espinosa-Ramos , Scott C. Hutchings , Yash Dixit , David Jin , Grace S. Ryan , Mieke Marsden , Sara R. Jaeger , Marlon M. Reis","doi":"10.1016/j.foodqual.2024.105377","DOIUrl":null,"url":null,"abstract":"<div><div>Data from online product reviews offers a novel avenue for the sensory characterisation of food. But, little research has investigated the quality of sensory information in the online reviews. The aim of this research was to investigate consumer online reviews as sources of sensory attributes of food products (starting with a minimum of 1000 online reviews per product), and to assess how the resulting sensory product profiles compare to profiles obtained in a central location test with 105 consumers using rate-all-that-apply (RATA) questions. A case study was conducted with five unflavoured coffee samples. A semi-automated approach, combining natural language processing and sensory science expertise was used to clean online review data, develop a sensory lexicon, and analyse the frequency of attributes used by consumers. It was possible to develop online review-based sensory product profiles and discriminate the five samples on this basis. Consumers used a small set of broad, mostly intensity related sensory terms (e.g. ‘Bold/rich’, ‘Strong/intense’, ‘Smooth’, ‘Weak/bland’) more frequently than descriptive terms. Canonical analysis showed high agreement between new method and RATA for product discrimination and between two group of descriptors. The first group (including ‘Coffee Flavor,’ ‘Rich in Flavor’, and ‘Smell of Coffee’) is associated with the intensity of flavour of coffee, while the second group describes characteristic flavour of coffee (including ‘Bold’, ‘Dark’ ‘Body’). Furthermore, care should be taken when implementing these findings in food categories with lower levels of consumer engagement, where consumer comments relating to sensory properties in online reviews may be less frequent.</div></div>","PeriodicalId":322,"journal":{"name":"Food Quality and Preference","volume":"125 ","pages":"Article 105377"},"PeriodicalIF":4.9000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Food Quality and Preference","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0950329324002799","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Data from online product reviews offers a novel avenue for the sensory characterisation of food. But, little research has investigated the quality of sensory information in the online reviews. The aim of this research was to investigate consumer online reviews as sources of sensory attributes of food products (starting with a minimum of 1000 online reviews per product), and to assess how the resulting sensory product profiles compare to profiles obtained in a central location test with 105 consumers using rate-all-that-apply (RATA) questions. A case study was conducted with five unflavoured coffee samples. A semi-automated approach, combining natural language processing and sensory science expertise was used to clean online review data, develop a sensory lexicon, and analyse the frequency of attributes used by consumers. It was possible to develop online review-based sensory product profiles and discriminate the five samples on this basis. Consumers used a small set of broad, mostly intensity related sensory terms (e.g. ‘Bold/rich’, ‘Strong/intense’, ‘Smooth’, ‘Weak/bland’) more frequently than descriptive terms. Canonical analysis showed high agreement between new method and RATA for product discrimination and between two group of descriptors. The first group (including ‘Coffee Flavor,’ ‘Rich in Flavor’, and ‘Smell of Coffee’) is associated with the intensity of flavour of coffee, while the second group describes characteristic flavour of coffee (including ‘Bold’, ‘Dark’ ‘Body’). Furthermore, care should be taken when implementing these findings in food categories with lower levels of consumer engagement, where consumer comments relating to sensory properties in online reviews may be less frequent.
期刊介绍：
Food Quality and Preference is a journal devoted to sensory, consumer and behavioural research in food and non-food products. It publishes original research, critical reviews, and short communications in sensory and consumer science, and sensometrics. In addition, the journal publishes special invited issues on important timely topics and from relevant conferences. These are aimed at bridging the gap between research and application, bringing together authors and readers in consumer and market research, sensory science, sensometrics and sensory evaluation, nutrition and food choice, as well as food research, product development and sensory quality assurance. Submissions to Food Quality and Preference are limited to papers that include some form of human measurement; papers that are limited to physical/chemical measures or the routine application of sensory, consumer or econometric analysis will not be considered unless they specifically make a novel scientific contribution in line with the journal''s coverage as outlined below.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
