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

What is the role of social interactions in the creation of price bubbles? Answering this question is often difficult, as it requires obtaining collective behavioural traces generated by the activity of a large number of actors. Cryptocurrencies, which only exist in digital form, offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid price increase followed by sharp decline; we hypothesise that these fluctuations are largely driven by the interplay between different social phenomena. In addition to analysing the exchange rates (price), we thus quantify three social signals about Bitcoin from large on-line data sets: volume of word-of-mouth communication in on-line social media, volume of information search, and user base growth. We find significant time-lagged correlations between pairs of these signals, most notably between price and volumes of information search and word of mouth. By using a vector autoregression, we identify two positive feedback loops that give rise to price bubbles: one driven by word of mouth, and the other by new Bitcoin adopters. This feedback mechanism implies that Bitcoin prices should experience unbound price growth in the absence of external stimuli. However, we also observe that spikes in information search, presumably linked to such external events, precede drastic price declines. Understanding the interplay between the socio-economic signals we measured can lead to applications beyond cryptocurrencies to other phenomena which leave digital footprints, such as on-line social network usage.