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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.
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We also viewed the results from a social science perspective, highlighting how the design choices of online trade platforms can exacerbate peer influence effects and market behavior. For instance, one existential threat to cryptocurrencies is dramatic fluctuations in traders’ willingness to buy or sell. The speculative nature of these markets — where many participants trade because they expect one or another currency to increase in value — can lead to bubbles and subsequent market crashes.
Interestingly, the design of the online exchanges may contribute to these bubbles and crashes if functionality, graphical user interfaces (GUIs), or application programming interfaces (APIs) promote collective excitement. Even small factors such as the prominent display of price history trends in the ticker chart — a feature common to all exchanges we compared — could plausibly encourage peer influence.
For online market designers, the message is that even minor changes in the systems that affect individual and collective behavior can have major social and economic impact.
Predicting Popularity and Following the Herd
The impact of collective behavior has long been studied by social scientists to understand why certain people, items, or options become more popular than others. One seemingly intuitive theory is that inherent value drives popularity. High-end cars or organic foods, it can be argued, are safer or healthier than alternatives. But another theory claims that popularity is driven by the “rich-get-richer” effect of cumulative advantage: Certain options — whether they’re diet sodas, financial services, or smartphone apps — become more popular not because they are higher quality, but because they are already relatively popular. In fact, it seems likely that popularity is not driven by either of these forces alone, but both together. Perhaps the rich get richer because attention leads to more attention: Traders might gain followers just by being displayed prominently on a website.
Most human behavior is the result of learning from other humans. It is this peer-to-peer socialization that produces fads, trends, and seismic shifts. Because these change patterns are common across many situations, they are somewhat predictable. Predictive analytics, already used in the areas of retail investment and cryptocurrency, can identify patterns and help anticipate social behaviors, trends, and meaning in online efforts.
Crowdsourcing and crowdfunding offer other examples of online peer influence, or “herd mentality.” It’s clear that viral ads, videos, and online recommendations have significant effects — positive and negative — on investment and purchase decisions. When researchers studied “herding” by traders who copy others’ investment decisions, they determined that markets can be manipulated as a result of this behavior.
A number of other observational studies, laboratory experiments, and small-scale field trials in finance and economics have examined peer influence in financial markets and identified evidence to explain price momentum, for example. We focused on the effects of small individual trades rather than large actions. Our work also builds on a growing area within the human-computer interaction (HCI) and computer-supported cooperative work (CSCW) communities involving the study of human collective behavior in online platforms.
Society is constantly changing, which means that behavior, supply chains, or trading data you collect today may not be applicable tomorrow. New tools and methods, along with the study of online behavior, offer some ways to make sense of these erratic online activities. And as any teenager knows, you can’t underestimate the role of peer influence.