CRYPTO CURRENCY PRICE PREDICTION USING SENTIMENT ANALYSIS

Dr. RAJESHWARI D , Dr. Ananthapadmanabha T

Cryptocurrency, Bitcoin, LSTM, Bi-Directional LSTM, Twitter data

A developing market, crypto currencies are becoming more and more important in the financial sector. The crypto currency market is an ideal research topic because of its low entrance barrier and high data availability. By applying sentiment analysis and machine learning techniques, it is possible to gain insights into the behavior of markets for the difficult work of stock market forecasting. Although there has been some prior research, the majority have only looked at the behavior of Bitcoin. This technique suggests using widely used machine learning tools and readily accessible social media data to forecast changes in the price of the Bitcoin cryptocurrency market. The findings demonstrate that cryptocurrency markets may be predicted using machine learning and sentiment analysis, with Twitter data being able to predict specific cryptocurrencies and outperforming other models. This system presents predictive model for forecasting the Bitcoin price movements using LSTM, Bi-Directional LSTM using sentiment analysis extracted from Twitter data. A review of the relevant literature and related works which this work expands upon is presented, in addition to an analysis of relevant techniques.

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"CRYPTO CURRENCY PRICE PREDICTION USING SENTIMENT ANALYSIS ", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.a310-a326, March-2023, Available :https://ijnrd.org/papers/IJNRD2303032.pdf

Volume 8 Issue 3, March-2023

Pages : a310-a326

Paper Reg. ID: IJNRD_188205

Published Paper Id: IJNRD2303032

Downloads: 000118889

Research Area: Computer Science & Technology 

Country: Mysuru, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303032

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303032

DOI: http://doi.one/10.1729/Journal.33411

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition