Abstract
This study conducted a real-time analysis of the health functional food market using big data. To assess the scope of big data in market analysis, big data of the health food category were compared and analyzed with actual market data. Data were first collected using a program to obtain data, through application programming interfaces, followed by SPSS to compare and analyze the actual market index and shopping search word data. The correlation between the online search data and the actual market was high, indicating that online search data can be used to predict the trend of the actual market. Various types of data, such as items and major functional ingredients, can be collected and analyzed through the program developed for this study, which is also used to predict the market trend. The results demonstrate how APIs can be used to predict market size in the food industry effectively.
Highlights
In March 2012, the Obama administration launched the Big Data Research and Development Initiative with a budget of 200 million USD (Jee and Kim, 2013)
This study investigated the similarity between the actual market performance of health functional food (HFF) and the frequency of big data shopping searches using the search term frequency in the shopping application programming interfaces (APIs) provided by NV, the top portal company in Korea
The three-year health food category data obtained through the NV API were separated by year and displayed using a
Summary
In March 2012, the Obama administration launched the Big Data Research and Development Initiative with a budget of 200 million USD (Jee and Kim, 2013). Abstract This study conducted a real-time analysis of the health functional food market using big data.
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