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http://hdl.handle.net/20.500.12188/30474
Title: | Using Centrality Measures to Extract Knowledge from Cryptocurrencies’ Interdependencies Networks | Authors: | Rusevski, Ivan Angelovski, Gorast Vodenska, Irena Chitkushev, Ljubomir Trajanov, Dimitar |
Issue Date: | 2023 | Publisher: | Springer Nature | Journal: | ICT Innovations 2022. Reshaping the Future Towards a New Normal: 14th International Conference, ICT Innovations 2022, Skopje, Macedonia, September 29–October 1, 2022, Proceedings | Abstract: | Is the rising price of Bitcoin affected by Ethereum’s fall? Are cryptocurrencies interconnected and are shifts in prices a consequence of said influence, or maybe social media plays a more significant role? To answer these questions, we create 7 networks using different approaches, each of them representing the relationship between 18 most popular cryptocurrencies in a distinct way. Additionally, by calculating centrality measures on the networks, we discover the currency that will be the first to spread their influence onto others. Moreover, these measures detects a currency with a high influence over the entire network, as well as the one that have the most “important” neighbors. Our results show that cryptocurrencies are indeed interrelated, especially the more popular ones, which also happens to be the most affected by the social media platforms. Ethereum is one of the fastest to affect the others when change in price occur, while both Ethereum and Bitcoin have extensive reach in the networks. | URI: | http://hdl.handle.net/20.500.12188/30474 |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
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