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Cryptocurrency Market Movement and Tendency Forecasting using Twitter Emotion and Information Quantity

Journal: International Journal of Trend in Scientific Research and Development (Vol.7, No. 2)

Publication Date:

Authors : ;

Page : 543-550

Keywords : Bitcoin; Augmented DisckyFilter; Coin markup;

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Abstract

Bitcoin was initially described to the public in a paper released in 2008 under the identity Satoshi Nakamoto. The first ever Bitcoin transaction took place on January 3, 2009. Its success paved the way for the development of similar digital currencies in the years that followed. There are more than 12,500 different cryptocurrencies, according to CoinMarketcap 2021. This is mostly owing to the extraordinary volatility of the market, which drew many individuals to take an interest and participate in it in the hopes of making money. Twitter has emerged as a common meeting place for those interested in cryptocurrencies. In a noteworthy move, Twitter announced on September 23, 2021, a new feature that would enable users to tip other users using their Bitcoin Lightning wallets. In spite of the fact that this new technology may have far reaching effects on our lives in the future, there is not a great deal of writing on the subject of cryptocurrencies. Even if there arent many rules in place yet for trading cryptocurrencies, a social media sentiment study might help fill in the gaps in our understanding of what influences bitcoin prices. In this study, we examine whether or not analyzing Twitter sentiment can reliably foretell changes in the value digital currencies. Seven of the most widely used cryptocurrencies have their own Twitter discussions and price histories gathered. After that was done, the Valence Aware Dictionary for Sentiment Reasoning was used to conduct an analysis of the datas emotional content VADER . We used the Augmented Dicky Fuller ADF , Kwiatkowski Phillips, Schmidt, and Shin KPSS , and Granger Causality tests to identify time series that were stationary. However, the bullishness ratio revealed that Ethereum and Polkadot prices were predicted despite the fact that swings in Bitcoin, Cardano, XRP, and DOGE prices tend to vary attitude. At last, we use Vector Autoregression VAR to look at the predictability of price returns, and we discover that two of the seven cryptocurrencies can have their prices predicted with a high degree of accuracy. Exactness of price forecasts for Polkadot and Ethereum, respectively, was 99.17 and 99.67 . A. Esakki Elango | E. Manohar ME | S. Vishnu Durga "Cryptocurrency Market Movement and Tendency Forecasting using Twitter Emotion and Information Quantity" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd55091.pdf Paper URL: https://www.ijtsrd.com.com/management/other/55091/cryptocurrency-market-movement-and-tendency-forecasting-using-twitter-emotion-and-information-quantity/a-esakki-elango

Last modified: 2023-07-20 21:50:43