Title

Bitcoin Price Forecasting: Linear Discriminant Analysis with Sentiment Evaluation

Document Type

Conference Proceeding

Source of Publication

2021 7th Annual International Conference on Arab Women in Computing (ArabWIC)

Publication Date

11-29-2021

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.

Publisher

Association for Computing Machinery (ACM)

Disciplines

Business

Indexed in Scopus

no

Open Access

no

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