소셜 빅데이터 분석을 통한 혼밥의 온라인 인식 연구

Abstract

This study aims to analyze the phenomenon of solo dining through big data analysis and derive the implications in terms of the 4Cs of marketing mix. For this purpose, the big data analysis solution Textom was used to collect and analyze blog and cafe posts related to ‘solo dining’ on Daum and Naver, as well as on Facebook. As a result, it was confirmed that the issues surrounding solo dining are shaped by a consumer-driven situation where the market follows the consumers in creating a new dining culture based on their voluntary demands and the need for it, rather than consumers merely choosing and purchasing products led by producers. Additionally, it was discovered that changes in travel culture after the COVID-19 pandemic are being revealed through solo dining. The phenomenon of solo dining demonstrated in this study serves as an indicator that it is not merely a temporary trend but rather a lifestyle centered around single-person households that is becoming universal. The collection and sharing of information about solo dining are actively driven by consumers through social media, indicating a proactive communication and development by consumers. This study holds academic significance as it moves beyond the negative perspectives of solo dining, such as loneliness or nutritional imbalance, and analyzes it from the perspective of changes in lifestyle leading to changes in consumer behavior. Furthermore, the confirmation of the 4Cs marketing theory through big data text mining analysis, as well as the presentation of alternatives for the activation of the solo dining industry, adds practical value to the research. From a practical standpoint,the study presents challenges and deficiencies in the food service industry for the increasing number of single-person households and solo diners.