Abstract
The main purpose of this research is to determine the association between the Twitter sentiment data and the price of West Texas Intermediate (WTI) crude oil platforms through a text mining technique. The research utilized data from Twitter and WTI crude oil closing prices data, during August 10th to November 8th, 2020. The Twitter Sentiment Analysis to analyze perception and employ Graph Association Analysis to explore the relationship of two selected platforms using data virtualization techniques. The initial results show the negative association, explaining that Twitter data and the WTI crude oil price have the relationship in the opposite direction. The results may support decisions in crude oil trading in the WTI market. Furthermore, the developed method might be suitable to forecast in other oil markets.
Metadata
| Item Type: | Book Section |
|---|---|
| Creators: | Creators Email / ID Num. Udchachone, Sarinthree sarinthree.u@acc.msu.ac.th Bhongchirawattana, Utis utis.s@acc.msu.ac.th Ngamtampong, Nantana nantana.n@acc.msu.ac.th Tosasukul, Jiraroj jirarojt@nu.ac.th |
| Subjects: | T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunication > Web servers. Internet |
| Divisions: | Universiti Teknologi MARA, Melaka > Jasin Campus > Faculty of Computer and Mathematical Sciences |
| Event Title: | International Conference on Emerging Computational Technologies (ICECoT 2021) |
| Event Dates: | 24 - 25 August 2021 |
| Volume: | 1 |
| Page Range: | pp. 42-47 |
| Keywords: | Crude oil prices; Graph association analysis; Twitter sentiment analysis |
| Date: | 2021 |
| URI: | https://ir.uitm.edu.my/id/eprint/86563 |
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