Skip to content

Latest commit

 

History

History
40 lines (23 loc) · 1.42 KB

File metadata and controls

40 lines (23 loc) · 1.42 KB

Correlation between BTC market movement based on twitter feeds related to bitcoin

by Tauseef Bashir

Executive summary

With the growth of market capitalization of cryptocurrencies (increased from $17 billion in 2017 to $2.25 trillion in 2021), cryptocurrencies remain incredibly volatile, with their value impacted by a multitude of factors: market trends, politics, technology…and Twitter. There have been instances where their prices were affected by tweets by famous personalities and the general public.

I plan to analyze trends over time, particularly the impact of social media on the price volatility of a crypto asset, such as Bitcoin (BTC).

Research Question

Research Question: Twitter Sentiment Analysis for Predicting Digital Assets Price Movements

Data Sources

BTC tweets dataset: https://www.kaggle.com/datasets/kaushiksuresh147/bitcoin-tweets

BTC historical data: https://www.kaggle.com/datasets/mczielinski/bitcoin-historical-data

Results

Please see the attached notebooks for setailed graphs and conclusions.

Notebooks

Please find attached the following two notebooks for bitcoin twitter and financial analysis:

  • BTC-Twitter-EDA.ipynb
  • BTC-analysis-using-Prophet-Pycarat.ipynb
References
  1. Time series prediction using Prophet in Python by Renu Khandelwal
  2. Housing pices EDA and Prediction by Ruchi Bhatia
  3. 88.9 r2_score with pycaret by Kerem Yucedag
  4. Pycaret documentation