ANALYZING SOCIAL MEDIA SENTIMENT TOWARD SPECIFIC COMMODITIES FOR FORECASTING PRICE MOVEMENTS IN COMMODITY MARKETS
This study adopts a systematic literature review to analyze social media sentiment towards specific commodities to enhance the accuracy of price movement forecasts in commodity markets. Drawing from the field of applied mathematics, the research gathered literature from Scopus, DOAJ, and Google Scho...
Saved in:
| Main Authors: | Mariono Mariono, Syaharuddin Syaharuddin, Sameer Ashraf, Sunday Emmanuel Fadugba |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Pattimura
2025-01-01
|
| Series: | Barekeng |
| Subjects: | |
| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/13086 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing agricultural commodity price forecasting with deep learning
by: R. L. Manogna, et al.
Published: (2025-07-01) -
The Research on the Impact of the Changes of Commodity Price Level in the World Commodity Exchanges on Variation of General Price Level
by: Algita Miečinskienė, et al.
Published: (2014-11-01) -
An integrated framework for multi-commodity agricultural price forecasting and anomaly detection using attention-boosted models
by: Eko Sediyono, et al.
Published: (2025-08-01) -
Using Futures Prices and Analysts’ Forecasts to Estimate Agricultural Commodity Risk Premiums
by: Gonzalo Cortazar, et al.
Published: (2025-01-01) -
A novel hybrid neural network-based volatility forecasting of agricultural commodity prices: empirical evidence from India
by: R. L. Manogna, et al.
Published: (2025-04-01)