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Contribution Details
Type | Conference Presentation |
Scope | Discipline-based scholarship |
Title | From social media to endogenous activity: Their effects on Bitcoin price bubbles and user adoption |
Organization Unit | |
Authors |
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Presentation Type | paper |
Item Subtype | Original Work |
Refereed | Yes |
Status | Published in final form |
Language |
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Event Title | Computational and Methodological Statistics |
Event Type | conference |
Event Location | London |
Event Start Date | December 11 - 2015 |
Event End Date | December 15 - 2015 |
Abstract Text | What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. We focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesise that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large datasets: price on online exchanges, volume of word-of-mouth communication in online social media, volume of information search and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin adopters. We also observe that spikes in information search, presumably linked to external events, precede drastic price declines. We further identify users within the Bitcoin transaction network, and show how the user adoption and endogenous economic activity (signalled by both: the economic transactions between them, and capital accumulation) makes this system a rather different one with respect to how it was originally envisioned. |
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