How Are Twitter Activities Related to Top Cryptocurrencies' Performance? Evidence from Social Media Network and Sentiment Analysis

Han Woo Park, Youngjoo Lee

Abstract


Cryptocurrencies have embraced Twitter as a major channel of
communication. Employing social network analysis and
sentiment analysis, this study investigates the Twitter-mediated
communication behaviors among cryptocurrencies. This study
determines whether a significant association exists between
cryptocurrencies' Twitter networks and their credit scores. Data
were drawn from the Twitter pages of several top
cryptocurrencies. The results indicate that reply–mention
networks had the densest structure, that the following–follower
network structure was correlated with the reply–mention
structure, and that the reply–mention and co–tweet networks
were positively correlated. The results also indicate that
cryptocurrencies' active networking strategies affected their
credit scores and more importantly, that cryptocurrencies
frequently linked with fellow currencies tended to have high
credit scores.

Keywords


cryptocurrency; Twitter; social network analysis; Weiss rating; sentiment analysis

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Print ISSN 1330-0288 | Online ISSN 1848-6096