Bitcoin Price Forecasting: Linear Discriminant Analysis with Sentiment Evaluation

doi:10.1145/3485557.3485561

Paper

Bitcoin Price Forecasting: Linear Discriminant Analysis with Sentiment Evaluation

Published Aug 25, 2021 · Ikhlaas Gurrib, Firuz Kamalov, Linda Smail

The 7th Annual International Conference on Arab Women in Computing in Conjunction with the 2nd Forum of Women in Research

UNKNOWN SJR score

5

Citations

0

Influential Citations

Full text

Semantic Scholar

Abstract

Cryptocurrencies such as bitcoin have garnered a lot of attention in recent months due to their meteoric rise. In this paper, we propose a new method for predicting the direction of bitcoin price using linear discriminant analysis (LDA) together with sentiment analysis. Concretely, we train an LDA-based classifier that uses the current bitcoin price information and Twitter headline news in order to forecast the next-day direction of bitcoin price. The proposed model achieves highly accurate results beating several benchmark targets. In particular, the proposed approach produces forecast accuracy of 0.828 and AUC of 0.840 on the test data.

Study Snapshot

Key takeawayThe proposed method using linear discriminant analysis and sentiment analysis effectively predicts bitcoin price direction, with a forecast accuracy of 0.828 and AUC of 0.840 on test data.

PopulationOlder adults (50-71 years)

Sample size24

MethodsObservational

OutcomesBody Mass Index projections

ResultsSocial networks mitigate obesity in older groups.

Sign up to use Study Snapshot

Consensus is limited without an account. Create an account or sign in to get more searches and use the Study Snapshot.

Create an account

Bitcoin Price Forecasting: Linear Discriminant Analysis with Sentiment Evaluation

Sign up to use Study Snapshot

References

Citations