Exploring Key Properties and Predicting Price Movements of Cryptocurrency Market Using Social Network Analysis

Kin-Hon HO*, Yun HOU, Michael GEORGIADES, Ken C.K. FONG

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

Abstract

The emerging cryptocurrency market is one of the largest financial markets in the world, with a market capitalization that is already surpassing the gross domestic product of many developed economies. Cryptocurrencies are increasingly being adopted as a means of transaction and ownership in the digital domain, particularly in areas like decentralized finance and non-fungible tokens. Known for its high volatility, this market offers investors the potential for higher returns than traditional financial markets like stocks, foreign exchange, and commodities. However, it remains underexplored in academic research. In this paper, we propose the use of social network analysis to effectively model and analyze the cryptocurrency market and conduct a comprehensive numerical study to explore its key properties, including correlation structure, topological characteristics, stability, and influence. Furthermore, we propose the use of centrality measures as novel indicators to improve the accuracy of cryptocurrency price movement predictions. Our research introduces a novel method for understanding and navigating the cryptocurrency market, enabling investors to integrate advanced analytical tools into their decision-making processes.
Original languageEnglish
Pages (from-to)65058-65077
Number of pages20
JournalIEEE Access
Volume12
Early online date4 May 2024
DOIs
Publication statusPublished - 6 May 2024

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Analytical models
  • Bitcoin
  • Centrality measures
  • Correlation
  • Cryptocurrency
  • cryptocurrency
  • Investment
  • price movement prediction
  • social network analysis
  • Social networking (online)
  • Terminology

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