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Information diffusion in referral networks: an empirical investigation of the crypto asset landscape

Author

Listed:
  • Srinidhi Vasudevan

    (University of Greenwich)

  • Anna Piazza

    (University of Greenwich)

  • Stefano Ghinoi

    (University of Greenwich
    University of Studi Modena e Reggio Emilia
    University of Helsinki
    Trieste)

Abstract

In the last decades, crypto assets have become particularly popular in financial markets. However, public awareness of the crypto asset landscape is rather limited, and usually associated with sensationalized media coverage of a handful of cryptocurrencies. Moreover, while users of crypto assets primarily collect information on Internet, there is a limited understanding of the relational (online) structures supporting the diffusion of information about these financial products. Therefore, the aim of this study is to uncover the structure of online information referral networks dedicated to crypto assets. By adopting a multi-method approach consisting of web scraping, web analytics, and social network analysis, we use data from the top 200 crypto assets by market capitalization to identify pivotal websites and the overall connectedness of the information referral networks. Our results show that social media and news channel sites play a key role in the information diffusion process, while market and trading sites signal innovation adoption. Overall, cryptocurrencies’ websites do not seem key in the referral network, as opposed to social media websites which, however, cannot be considered mature hubs because of their low connectivity.

Suggested Citation

  • Srinidhi Vasudevan & Anna Piazza & Stefano Ghinoi, 2025. "Information diffusion in referral networks: an empirical investigation of the crypto asset landscape," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(1), pages 41-58, February.
    • Handle: RePEc:spr:qualqt:v:59:y:2025:i:1:d:10.1007_s11135-024-01978-8
    DOI: 10.1007/s11135-024-01978-8
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    References listed on IDEAS

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