Unveiling the influence of steemit conversations on a bitcoin bubble

Hatem Mabrouk, Federico Trigos and Francisco Valderrey

Journal of Management Analytics, 2026, vol. 13, issue 2, 199-216

Abstract: Financial market speculative bubbles strongly impact the economy, like the June 2017-February 2018 Bitcoin bubble. Several factors often fuel them, and the role of online communities in influencing such market dynamics is unclear. Understanding the interaction between online discourse and cryptocurrency market behaviour is essential for exploring whether online communities influence speculative market dynamics. While prior research has focused on major platforms like X or Reddit, few studies have systematically analysed blockchain-based platforms’ online behaviour in relation to these speculative bubbles. This paper analyses the relationship between the Steemit platform discussion dynamics and the Bitcoin bubble of 2017-2018. Term frequency analysis and correlation methods were used to explore how key terms in Steemit discussions evolved and whether they corresponded with Bitcoin's price changes during the bubble. The contribution of this research is to enhance the understanding of speculative events for risk management and policy decisions by exploring whether there are significant relations among online discussions over market behaviour and investor sentiment. The analysis indicates that while Steemit's discussions largely mirrored the ongoing market sentiment, specific terms exhibited strong positive correlations with Bitcoin price fluctuations, highlighting the role of particular discussions in amplifying speculative sentiment. These results suggest that online discourse may contribute to investor sentiment without necessarily driving market dynamics. This study provides valuable insights into the role of blockchain-based platforms in speculative events, offering implications for risk management and financial policy.

Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/23270012.2026.2625747 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjmaxx:v:13:y:2026:i:2:p:199-216

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjma20

DOI: 10.1080/23270012.2026.2625747

Access Statistics for this article

Journal of Management Analytics is currently edited by Li Xu

More articles in Journal of Management Analytics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().