- 권한신청
- P-ISSN1738-6764
- E-ISSN2093-7504
- KCI
ISSN : 1738-6764
Relations Between Paprika Consumption and Unstructured Big Data, and Paprika Consumption Prediction
오은화 (충북대)
조완섭 (충북대학교)
나스리디노프 아지즈 (충북대학교)
유관희 (충북대학교)
나형철 (충북대학교 빅데이터협동과정)
Abstract
It has been reported that large amounts of information on agri-foods were delivered to consumers through television and social networks, and the information may influence consumers’ behavior. The purpose of this paper was first to analyze relations of social network service and broadcasting program on paprika consumption in the aspect of amounts to purchase and identify potential factors that can promote paprika consumption; second, to develop prediction models of paprika consumption by using structured and unstructured big data. By using data 2010-2017, cross-correlation and time-series prediction algorithms (autoregressive exogenous model and vector error correction model), statistically significant correlations between paprika consumption and television programs/shows and blogs mentioning paprika and diet were identified with lagged times. When paprika and diet related data were added for prediction, these data improved the model predictability. This is the first report to predict paprika consumption by using structured and unstructured data.
- keywords
- Agri-food, Prediction, Unstructured Big Data, Paprika.
- 다운로드 수
- 조회수
- 0KCI 피인용수
- 0WOS 피인용수