The cryptocurrency industry has evolved rapidly in recent years, and it is increasingly popular as a convenient tool to complement the traditional stock and futures exchanges. Accurate market research enables traders to make more informed decisions and benefit from their investments. Our objective is to introduce a web platform for aggregating various types of cryptocurrency data, both on- and off-chain. Its novelty lies in offering a visual representation of market data analysis, which is driven by multi-modal data fusion and representation techniques, as well as artificial intelligence. We propose a full-stack framework that consists of a front-end web application for user interaction and visualization, and a backend server for data fetching, preprocessing, and analysis. In our implementation, we used data from the cryptocurrency market, on-chain statistics, and textual data from social media, to create a deep-learning-based market trend model. For market prediction, our data analysis module processed high-frequency vocabulary extracted from social media, sentiment analysis of social media content, historical price trend, and historical hash rates. Investors and market analysts can benefit from our platform by directly observing the dynamic of multi-modal cryptocurrency data and easily exploring market trends, generated by our market prediction model delivered by a front-end application. The complete implementation can be found in our publicly available GitHub link upon request.
CITATION STYLE
Zhu, N., Yang, F., Zhu, M., Sun, X., & Cheng, I. (2021). Data-enabled cryptocurrency market analysis and visualization platform. In International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing 2021, CGVCVIP 2021, Connected Smart Cities 2021, CSC 2021 and Big Data Analytics, Data Mining and Computational Intelligence 2021, BIGDACI 2021 - Held at the 15th Multi-Conference on Computer Science and Information Systems, MCCSIS 2021 (pp. 133–137). IADIS. https://doi.org/10.33965/mccsis2021_202107c017
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