Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Cryptocurrency ecosystems have experienced rapid growth, yet most available platforms emphasize trading, speculation, and price monitoring rather than fundamental understanding of blockchain technologies. Additionally, short-term price movements in cryptocurrency markets are highly influenced by news sentiment and volatility. The system integrates real-time crypto news sentiment with machine learning models to predict short-term market movement direction and volatility risk for the next 15 minutes and 1 hour. A Random Forest model is used as a baseline, while a Long Short-Term Memory (LSTM)network captures temporal dependencies. The platform also incorporates an Explainable AI (XAI) layer
"Crypto Geeks: Crypto Education and Research Platform with Predictive Sentiment–Price Modelling and Explainable AI ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.a922-a932, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604125.pdf
Downloads:
00047
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator