Cryptocurrency Price Prediction using Twitter Sentiment Analysis

Haritha GB, Sahana N. B
3/3/2023
q-fin.STcs.AIcs.CL

No official code found. Best implementation: Aaron-Paul/Bitcoin-Price-Twitter-Sentiment-Analysis (35 stars, last commit 2021-03-02).

Abstract

The cryptocurrency ecosystem has been the centre of discussion on many social media platforms, following its noted volatility and varied opinions. Twitter is rapidly being utilised as a news source and a medium for bitcoin discussion. Our algorithm seeks to use historical prices and sentiment of tweets to forecast the price of Bitcoin. In this study, we develop an end-to-end model that can forecast the sentiment of a set of tweets (using a Bidirectional Encoder Representations from Transformers - based Neural Network Model) and forecast the price of Bitcoin (using Gated Recurrent Unit) using the predicted sentiment and other metrics like historical cryptocurrency price data, tweet volume, a user's following, and whether or not a user is verified. The sentiment prediction gave a Mean Absolute Percentage Error of 9.45%, an average of real-time data, and test data. The mean absolute percent error for the price prediction was 3.6%.

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Code Implementations(1)

Aaron-Paul/Bitcoin-Price-Twitter-Sentiment-AnalysisCommunity73%

Bitcoin price prediction using twitter sentiment analysis

3516Java, PythonJan 6, 20215 years ago
bitcoinpredictionsentiment-analysis

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Cite this paper

@article{gb2023cryptocurrency,
  title  = {Cryptocurrency Price Prediction using Twitter Sentiment Analysis},
  author = {Haritha GB and Sahana N. B},
  year   = {2023},
  eprint = {2303.09397},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2303.09397v1}
}

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