Martha D. Calvert, Elizabeth Cole, Clinton L. Neill, Amanda C. Stewart, Susan R. Whitehead, Jacob Lahne
{"title":"使用新颖的文本挖掘方法探索苹果酒网站描述","authors":"Martha D. Calvert, Elizabeth Cole, Clinton L. Neill, Amanda C. Stewart, Susan R. Whitehead, Jacob Lahne","doi":"10.1111/joss.12854","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <p>Rapid methods of text analysis are increasingly important tools for efficiently extracting and understanding communication within the food and beverage space. This study aimed to use frequency-based text mining and biterm topic modeling (BTM) as tools for analyzing how cider products are communicated and marketed on cider-producer websites for products made in Virginia, Vermont, and New York. BTM has been previously used to explore topics in small corpora of text data, and frequency-based text mining is efficient for exploring patterns of text across different documents or filters. The present dataset comprised 1115 cider products and their website descriptions extracted from 124 total cider-producer websites during 2020 and 2021. Results of the text mining analyses suggest that cider website descriptions emphasize food-pairing, production, and sensory quality information. Altogether, this research presents the text mining approaches for exploring food and beverage communication.</p>\n </section>\n \n <section>\n \n <h3> Practical applications</h3>\n \n <p>This research will be valuable to stakeholders in the United States' cider industry by providing relevant insight as to how cider marketing and sensory communication varies based on extrinsic product factors, such as geography and packaging. This research also demonstrates the efficiency and potential of text mining tools for exploring language and communication related to foods, beverages, and sensory quality. Further, this research provides a framework for extracting sensory-specific language from a large corpus of data, which may be adopted by other researchers wishing to apply rapid descriptive methods in the sensory, quality, and consumer research fields.</p>\n </section>\n </div>","PeriodicalId":17223,"journal":{"name":"Journal of Sensory Studies","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/joss.12854","citationCount":"1","resultStr":"{\"title\":\"Exploring cider website descriptions using a novel text mining approach\",\"authors\":\"Martha D. Calvert, Elizabeth Cole, Clinton L. Neill, Amanda C. Stewart, Susan R. Whitehead, Jacob Lahne\",\"doi\":\"10.1111/joss.12854\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <p>Rapid methods of text analysis are increasingly important tools for efficiently extracting and understanding communication within the food and beverage space. This study aimed to use frequency-based text mining and biterm topic modeling (BTM) as tools for analyzing how cider products are communicated and marketed on cider-producer websites for products made in Virginia, Vermont, and New York. BTM has been previously used to explore topics in small corpora of text data, and frequency-based text mining is efficient for exploring patterns of text across different documents or filters. The present dataset comprised 1115 cider products and their website descriptions extracted from 124 total cider-producer websites during 2020 and 2021. Results of the text mining analyses suggest that cider website descriptions emphasize food-pairing, production, and sensory quality information. Altogether, this research presents the text mining approaches for exploring food and beverage communication.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Practical applications</h3>\\n \\n <p>This research will be valuable to stakeholders in the United States' cider industry by providing relevant insight as to how cider marketing and sensory communication varies based on extrinsic product factors, such as geography and packaging. This research also demonstrates the efficiency and potential of text mining tools for exploring language and communication related to foods, beverages, and sensory quality. Further, this research provides a framework for extracting sensory-specific language from a large corpus of data, which may be adopted by other researchers wishing to apply rapid descriptive methods in the sensory, quality, and consumer research fields.</p>\\n </section>\\n </div>\",\"PeriodicalId\":17223,\"journal\":{\"name\":\"Journal of Sensory Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/joss.12854\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Sensory Studies\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/joss.12854\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Sensory Studies","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/joss.12854","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Exploring cider website descriptions using a novel text mining approach
Rapid methods of text analysis are increasingly important tools for efficiently extracting and understanding communication within the food and beverage space. This study aimed to use frequency-based text mining and biterm topic modeling (BTM) as tools for analyzing how cider products are communicated and marketed on cider-producer websites for products made in Virginia, Vermont, and New York. BTM has been previously used to explore topics in small corpora of text data, and frequency-based text mining is efficient for exploring patterns of text across different documents or filters. The present dataset comprised 1115 cider products and their website descriptions extracted from 124 total cider-producer websites during 2020 and 2021. Results of the text mining analyses suggest that cider website descriptions emphasize food-pairing, production, and sensory quality information. Altogether, this research presents the text mining approaches for exploring food and beverage communication.
Practical applications
This research will be valuable to stakeholders in the United States' cider industry by providing relevant insight as to how cider marketing and sensory communication varies based on extrinsic product factors, such as geography and packaging. This research also demonstrates the efficiency and potential of text mining tools for exploring language and communication related to foods, beverages, and sensory quality. Further, this research provides a framework for extracting sensory-specific language from a large corpus of data, which may be adopted by other researchers wishing to apply rapid descriptive methods in the sensory, quality, and consumer research fields.
期刊介绍:
The Journal of Sensory Studies publishes original research and review articles, as well as expository and tutorial papers focusing on observational and experimental studies that lead to development and application of sensory and consumer (including behavior) methods to products such as food and beverage, medical, agricultural, biological, pharmaceutical, cosmetics, or other materials; information such as marketing and consumer information; or improvement of services based on sensory methods. All papers should show some advancement of sensory science in terms of methods. The journal does NOT publish papers that focus primarily on the application of standard sensory techniques to experimental variations in products unless the authors can show a unique application of sensory in an unusual way or in a new product category where sensory methods usually have not been applied.