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What is the role of social interactions in the creation of price bubbles?Answering this question requires obtaining collective behavioural tracesgenerated by the activity of a large number of actors. Digital currencies offera unique possibility to measure socio-economic signals from such digitaltraces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin hasexperienced periods of rapid increase in exchange rates (price) followed bysharp decline; we hypothesise that these fluctuations are largely driven by theinterplay between different social phenomena. We thus quantify foursocio-economic signals about Bitcoin from large data sets: price on on-lineexchanges, volume of word-of-mouth communication in on-line social media,volume of information search, and user base growth. By using vectorautoregression, we identify two positive feedback loops that lead to pricebubbles in the absence of exogenous stimuli: one driven by word of mouth, andthe other by new Bitcoin adopters. We also observe that spikes in informationsearch, presumably linked to external events, precede drastic price declines.Understanding the interplay between the socio-economic signals we measured canlead to applications beyond cryptocurrencies to other phenomena which leavedigital footprints, such as on-line social network usage.

The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy