LSTM-Based Analysis of Company Sentiments Regarding Cryptocurrencies

Authors

  • Zelal Su Mustafaoglu
  • Nolan Bogumill

Keywords:

cryptocurrencies, bitcoin, Sentiment Analysis, Financial Reporting, Natural Language Processing

Abstract

This study proposes an LSTM-based model to analyze company sentiments toward cryptocurrencies. The model was trained on a dataset that was collected by downloading 10-K files of 277 companies from the SEC Edgar Database and extracting sentences containing keywords related to cryptocurrencies. It achieved 99% accuracy on the training set and 83.59% accuracy on the testing set. By analyzing the relationship between company sentiment and price, the proposed model can be used to predict the price of cryptocurrencies. This study can also be extended to determine companies' intentions in disclosing the use of cryptocurrencies in their financial statements.

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Published

2022-05-05

Issue

Section

Professional Programs