Full metadata
Title
Predicting Bitcoin Price Trend using Sentiment Analysis
Description
In this paper I defend the argument that public reaction to news headlines correlates with the short-term price direction of Bitcoin. I collected a month's worth of Bitcoin data consisting of news headlines, tweets, and the price of the cryptocurrency. I fed this data into a Long Short-Term Memory Neural Network and built a model that predicted Bitcoin price for a new timeframe. The model correctly predicted 75% of test set price trends on 3.25 hour time intervals. This is higher than the 53.57% accuracy tested with a Bitcoin price model without sentiment data. I concluded public reaction to Bitcoin news headlines has an effect on the short-term price direction of the cryptocurrency. Investors can use my model to help them in their decision-making process when making short-term Bitcoin investment decisions.
Date Created
2020-05
Contributors
- Steinberg, Sam (Author)
- Boscovic, Dragan (Thesis director)
- Davulcu, Hasan (Committee member)
- Computer Science and Engineering Program (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Extent
19 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2019-2020
Handle
https://hdl.handle.net/2286/R.I.56421
Level of coding
minimal
Cataloging Standards
System Created
- 2020-04-18 12:02:22
System Modified
- 2021-08-11 04:09:57
- 3 years 3 months ago
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