Ever since the 19th century when European sociologists Auguste Comte and Adolphe Quetelet began using the term “social physics,” researchers have struggled to apply statistical methods to the social sciences.
In his new book, Social Physics: How Good Ideas Spread — The Lessons from a New Science, Alex “Sandy” Pentland, the director of MIT’s Human Dynamics Laboratory, says he thinks he and his colleagues have developed a formula that will not only accurately predict social behavior but also potentially impact commercial outcomes.
For example, he says there is proof that sharing with the right people on social networks can boost stock trading returns.
Pentland and Dr. Yaniv Altshuler, an Israeli serial entrepreneur who spent three years as a post-doc associate at MIT Media Lab, have been crunching data on eToro, a social investment network that empowers almost four million users in more than 170 countries. The site, which was co-founded by Yoni Assia, a speaker at Web Summit in Dublin November 4th to 6th, encourages novices to try their luck by allowing them to see how the more experienced traders trade and then copy them.
The premise — and the network set-up — intrigued Altshuler and Pentland, who also directs the MIT Media Lab Entrepreneurship Program and co-leads the World Economic Forum Big Data and Personal Data initiatives. (In 2012 Forbes named Pentland one of the “seven most powerful data scientists in the world,” along with the Google founders. He is considered a pioneer in computational social science, organizational engineering, image understanding, and modern biometrics.)
As people engage more with social networking sites, there is always the danger that they become “echo chambered”; that is, they reflect a “group think” mentality that leads people to follow a group consensus rather than critically evaluate information, Altshuler said in an interview with Informilo. Other potential pitfalls include making decisions without any guidance from the social network or following “gurus” who provide them with bad information. The challenge is how to avoid these errors and maximize the “wisdom of the crowd.”
Working with eToro, Altshuler and Pentland (who are not paid by eToro and do not own stakes in the company) distributed $20 trading coupons to thousands of active financial traders on the platform. Matches between traders and recommendations were based on an algorithm designed to optimize information flow within the network. The relatively small number of coupons was enough to move the network away from“groupthink,” and as a consequence, the entire trading community — not just the coupon users — saw a significant increase in their rate of return.
Networks Work As A Filter
But it was those who culled their information from the widest range of strategies who turned out to be the biggest winners, earning a 30% better return on their investments.
“We showed that we can actually use social physics to alter trading performance,” says Altshuler, who has a PhD in Computer Science from Israel’s Technion and specializes in collective intelligence and swarm algorithms.
The study demonstrated how an efficient collaborative trading community can be formed by carefully balancing the complex mixture of “trend setters” and “bellwethers” who govern the behavior of the crowd, he says. “Networks work as a filter that can filter out the noise and amplify the high-quality information. It comes down to the topology of the network; the way it is structured influences the way it assimilates information.”
Laws That Govern How People Interact In Groups
The academics are working with eToro to use the tool they developed to deploy a service that will do “online tuning of the community” to optimize results.
In his book Pentland also discusses experiments with other companies, including a bank and an IT consultancy, and describes how the performance of employees was boosted by using the same principles as the eToro experiment: creating opportunities for a group of disparate people to network. According to the book even a city’s GDP turns out to be highly correlated with opportunities for face-to-face encounters with a diverse group.
“Communities and people are very unpredictable, they are a great example of a complex system,” says Altshuler. But, he says, it turns out “there are a few mathematical laws that govern the way people interact in groups. And when you know these laws it allows you to do great stuff.”
The experience of traders on eToro’s network is proof of that, he says. “In the past stock trading was a zero-sum game controlled by players like big banks, but now, by combining their knowledge, people at the bottom of the food chain can improve their position, provided that the information network they create is an efficient one.”