Analyzing social media reactions to the FTX crisis: Unraveling the spillover effect on crypto markets

Chunsik Lee, Suan Lee, Junga Kim, Joon Soo Lim

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, we analyzed social media conversations during the unfolding of the FTX crisis, the biggest cryptocurrency scandal in United States history. Drawing on the accessibility-diagnosticity framework, we examined the negative spillover effect of the crisis using a natural language processing approach. We specifically assessed whether there was a negative spillover from FTX to other crypto entities with different levels of diagnostic attribute similarity. We collected a large corpus of Twitter conversations related to the FTX collapse in 2022 and used the association rule analysis to determine the association between FTX and other crypto entities. Our analysis revealed that the number of tweets mentioning FTX and other crypto entities changed in line with a series of real-world events during the FTX crisis. The negative spillover of the FTX crisis occurred primarily during the first 10 days as the FTX scandal unfolded. The results indicated that the FTX crisis spilled over to highly accessible and diagnostic crypto entities, such as Binance, Bitcoin, and the cryptocurrency industry in general. On the other hand, less accessible and less diagnostic crypto entities/currencies like Ethereum and Coinbase did not experience negative spillover from the scandal.

Original languageEnglish (US)
Article numbere12577
JournalJournal of Contingencies and Crisis Management
Volume32
Issue number2
DOIs
StatePublished - Jun 2024

Keywords

  • association rules
  • crisis attribute
  • crisis spillover
  • natural language processing
  • sentiment analysis

ASJC Scopus subject areas

  • Management Information Systems
  • Management, Monitoring, Policy and Law

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