Unstructured Data Analysis Research for Vegan Beauty Trends and Consumer Awareness Survey

Abstract

This study used unstructured data to analyze the various factors and relationships that influence consumers’ perception and behavior on vegan beauty, and predicted the future prospects of vegan beauty. The analysis results are as follows: First, in the keyword analysis related to vegan beauty, clean beauty and beebeuty appeared as the top main words, and cosmetics, ampoule, skin, double cream, animal raw material experiment, dalba, raw material use, etc. were followed. Second, as a result of performing TF-IDF analysis, ampoule, clean beauty, double cream, dalba, collagen, beebeuty, animal raw material experiment, and cosmetics appeared in order. Third, as a result of analyzing 50 keywords related to vegan beauty through centrality analysis and semantic network analysis, clean beauty, beebeuty, cosmetics, double cream, recommendation, ampoule, skin, animal raw material experiment, and dalba showed the most influence, and in the eigenvector centrality analysis, clean beauty, beebeuty, cosmetics, and double cream showed high values in order. Fourth, as a result of grouping 50 keywords related to vegan beauty derived through CONCOR analysis, the first group was keywords related to the attributes of vegan beauty, the second group was keywords related to vegan beauty products, the third group was keywords related to vegan beauty marketing, and the fourth group was keywords related to beauty care. Through these analysis results, we present the current situation and future possibilities of vegan beauty, and hope that it will help strengthen the competitiveness of vegan beauty brands and establish marketing strategies for vegan beauty brands.