As it turns out, popularity isn’t a concern for just high school students and rock stars. According to recent research, economic and social decisions rely on perceptions of popularity, too — especially online. Peer influence can have a huge effect on purchasing decisions, investments, and markets.
A three-year study of cryptocurrency markets — begun long before the recent spate of cryptocurrency hacks — dissected the dynamics of cyber-currency markets. The goal was to assess traders’ behavior and how susceptible they are to the actions of others. The findings are instructive for other online business behavior, as well — for instance, why consumers buy a particular brand, or why they follow someone on social media.
The results, published by Peter M. Krafft, Nicolás Della Penna, and myself in a January working paper, not only demonstrate the volatility of cryptocoins and the need for extreme caution when buying and investing, but also offer insights that can be used to anticipate and avoid future disruptive business events.
The research may help us understand more about how market fads and bubbles get started, and how much peers influence consumer behavior. As businesses increase their investments in social media marketing, they need better guidance about what works best and how to analyze their data. Moreover, as the online world becomes more complex — with crowdsourcing platforms and bots invading public spaces — these findings can help provide a compass to navigate the landscape.
Lessons Learned From Cryptocurrency Bubbles
Our online experiment of cryptocurrency traders used bots that executed over 100,000 trades, costing less than a penny each, in 217 cryptocurrencies over the course of six months. Analysis reveals that traders are very susceptible to peer influences.
For example, individual buy actions led to short-term increases in subsequent buy-side activity hundreds of times the size of our interventions. By simulating market bubbles, we demonstrated that even trades worth just fractions of a penny can influence the nature of other, much larger trades. Specifically, we observed an approximately 2% increase in buying activity after our interventions, and a cumulative effect 500 times the size of our interventions. While an increase of 2% might seem small for an individual action, in a large marketplace, this amount is not trivial.