A Model for Nowcasting Commodity Price based on Social Media Data 


Vol. 44,  No. 12, pp. 1258-1268, Dec.  2017
10.5626/JOK.2017.44.12.1258


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  Abstract

Capturing real-time daily information on food prices is invaluable to help policymakers and development organizations address food security problems and improve public welfare. This study analyses the possible use of large-scale online data, available due to growing Internet connectivity in developing countries, to provide updates on food security landscape. We conduct a case study of Indonesia to develop a time-series prediction model that nowcasts daily food prices for four types of food commodities that are essential in the region: beef, chicken, onion and chilli. By using Twitter price quotes, we demonstrate the capability of social data to function as an affordable and efficient proxy for traditional offline price statistics.


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  Cite this article

[IEEE Style]

(. Kim, M. Cha, J. G. Lee, "A Model for Nowcasting Commodity Price based on Social Media Data," Journal of KIISE, JOK, vol. 44, no. 12, pp. 1258-1268, 2017. DOI: 10.5626/JOK.2017.44.12.1258.


[ACM Style]

(Jaewoo Kim, Meeyoung Cha, and Jong Gun Lee. 2017. A Model for Nowcasting Commodity Price based on Social Media Data. Journal of KIISE, JOK, 44, 12, (2017), 1258-1268. DOI: 10.5626/JOK.2017.44.12.1258.


[KCI Style]

김재우, 차미영, 이종건, "소셜 데이터 기반 실시간 식자재 물가 예측 모형," 한국정보과학회 논문지, 제44권, 제12호, 1258~1268쪽, 2017. DOI: 10.5626/JOK.2017.44.12.1258.


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