SMU Office of Research – According to the concept of paying it forward, help a stranger and you make that person more likely to help another stranger. People’s words and actions are like stones thrown into a lake, which form ripple effects throughout their networks of family members, friends and even distant acquaintances and complete strangers.
“We’re all connected to one another and influence one another,” says Professor Michael Macy, who visited the Singapore Management University (SMU) School of Information Systems in early July this year. “A lot of what you think and believe is actually shaped by your environment, the people you interact with, and what they believe.”
As the director of the Social Dynamics Laboratory at Cornell University in the United States, Professor Macy’s research focuses on social patterns, including the rise and fall of fads and the spread of both generous and anti-social behaviour.
Birds of a feather flock together
Your friends’ attitudes and opinions, for instance, may have a far greater impact on your own beliefs than your socioeconomic background, age or gender, according to a paper, “Why Do Liberals Drink Lattes?”, co-written by Professor Macy and his doctoral students Daniel DellaPosta and Shi Yongren, published in the American Journal of Sociology.
Inspired by the popular but anecdotal accounts of connections between one’s political beliefs and lifestyle choices—such as ‘latte-drinking liberals’ and ‘bird-hunting conservatives’—the researchers used data from a national survey in the US called the General Social Survey to investigate if such connections really existed, and, if so, what the possible explanations would be.
Their research, which included combing through 28 editions of the survey conducted between 1972 and 2010, uncovered 14,436 statistically-significant lifestyle connections, both between people’s political beliefs and their lifestyle choices, as well as between the choices.
Scientists tend to explain people’s beliefs and behaviour as a consequence of their demographic attributes, such as their age, gender and ethnicity. If many old people like opera, it makes more sense to say that the age caused the preference, rather than vice versa.
But when Professor Macy and the students factored such demographic attributes into their statistical models, many of the lifestyle connections were still left unexplained. He believes that the gap can be explained by social influence, which is not captured in the survey and, for that matter, in almost all other surveys.
“Our big argument is that the demographic effects could be spurious or largely spurious due to the unmeasured effects of social influence,” he argues. “We leave out of survey samples people’s friends, neighbours, family, co-workers and roommates, all of whom influence our opinions and beliefs.”
To investigate the impact of social influence, he and his students built a simple computer model in which a population of simulated ‘agents’ interact repeatedly. Each ‘agent’ was armed with five fixed demographic attributes and 20 changeable attributes, such as political opinions and lifestyle preferences. They could also selectively adopt the opinions of their neighbours, in an approximation of social influence.
In fact, the simulation showed that when social influence was switched ‘on’, it greatly amplified demographic effects that were previously extremely weak. The results suggest that our initially minor preferences and lightly-held beliefs could strengthen and harden over time, either because people we like share the same attitudes, or because people we dislike have opposite ones, or both.
Our actions are ‘contagious’
Such social influence extends to our actions too. In a pair of papers, “The Social Contagion of Generosity” and “The Social Contagion of Antisocial Behaviour”, Professor Macy looked at whether and how helpful and harmful behaviour might be spread. The papers were co-written with his student, Milena Tsvetkova (now at the Oxford Internet Institute), and published in the PLoS ONE and Sociological Science journals respectively.
“We found that you’re more likely to pass it on, both when you’re helped and when you’re harmed,” he notes. “When you help someone, you’re not just helping them, you’re also helping the people downstream. The same thing holds when you hurt someone. If people understand how their own behaviour can change others’ behaviour, they might exercise more care.”
For the paper on antisocial behaviour, 750 people were recruited to play an online game where they could earn money by completing a ten-minute task. Divided into several chains of players, each player could choose to take some money from the next player’s earnings, in effect ‘harming’ that person. All of them were also told if the person before them had harmed them in the same way.
Through this study, Professor Macy discovered that observing high levels of antisocial behaviour did not make a person more likely to harm others. If a person sees that other people are not being antisocial, on the other hand, he is also less likely to indulge in such behaviour.
The paper on generosity also uncovered the complex effects of observing helpful behaviour. When people see a few instances of others being helpful, they become more willing to help. But, perhaps counter-intuitively, when they see many other people being helpful, they become less likely to help, possibly because they think someone else will step up.
Professor Macy plans to probe more deeply into how generosity spreads. A follow up study will tease apart whether the intention to help is sufficient, or must one also benefit from it, to make the helping behaviour ‘contagious’.
Social media, social influence
His research is expanding in other directions too. In the works is a website where people can type in any cultural entity and find out the extent to which it appeals to liberals or conservatives. He is also using data from Twitter, as well as Amazon and Barnes & Noble online purchases, to explore broader patterns of culture’s political polarisation.
“That’s the great thing about social media,” he muses. “Surveys give us retrospective data about independent individuals, but now we have population-scale time-stamped data on individuals and their network neighbours, in social networks of millions of people from all over the world.”
By developing statistical models that help to explain the relationship between social influence and human behaviour, Professor Macy hopes that his research will lead to further understanding in the field of social dynamics and, in effect, pay it forward.
By Feng Zengkun