Nowcasting commodity prices using social media
Open accessAbstract
Gathering up-to-date information on food prices is critical in developing regions, as it allows policymakers and development practitioners to rely on accurate data on food security. This study explores the feasibility of utilizing social media as a new data source for predicting food security landscape in developing countries. Through a case study of Indonesia, we developed a nowcast model that monitors mentions of food prices on Twitter and forecasts daily price fluctuations of four major food commodities: beef, chicken, onion, and chilli. A longitudinal test over 15 months of data demonstrates that not only that the proposed model accurately predicts food prices, but it is also resilient to data scarcity. The high accuracy of the nowcast model is attributed to the observed trend that the volume of tweets mentioning food prices tends to increase on days when food prices change sharply. We discuss factors that affect the veracity of price quotations such as social network-wide sensitivity and user influence.
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It is possible to distill relevant signals from mobile phones, credit card transactions, and social media data.
“For real-time and near-term systems, it is possible to distill relevant signals from mobile phones, credit card transactions, and social media data [171,434,645].”
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- Authors
- Kim, J., Cha, M., & Lee, J. G.
- Affiliations
- Graduate School of Culture Technology, Korea Advanced Institute of Science & Technology, Daejeon, South Korea
- Korea Advanced Institute of Science and Technology (KR)
- United Nations (US)
- ORCID
- Cha, Meeyoung
- Venue
- PeerJ Computer Science
- Publisher
- PeerJ
- Published
- 2017-07-31
- Volume
- 3
- Pages
- e126
- ISSN
- 2376-5992 (ISSN-L)
- OpenAlex
- W2741068695
- Cited by
- 25
- References
- 29
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 1 · 2023: 3 · 2022: 7 · 2021: 3 · 2020: 2 · 2019: 3 · 2018: 2
- FWCI
- 3.44
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PeerJ Computer Science (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Industrial Technology Innovation Program (10073144)
- Developing machine intelligence based conversation system
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economics of Agriculture and Food Markets
- Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
- Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
- Keywords
- nowcasting, food prices, social media, Twitter, food security, commodity price forecasting, data scarcity, user influence, Indonesia
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