The Art Of Quantitative Methods In Sociology
On September 25, the Fall Distinguished Speakers Series kicked off in the Network Science Institute at Northeastern University. The very first invited speaker, Nicholas A. Christakis, presented his work on social networks interventions. Nicholas is a sociologist and physician, directing the Human Nature Lab at Yale University. He brought quantitative methods to the social networks to study social phenomena. He was named in the Time magazine's list of the 100 most influential people in the world in 2009. He was also named by Foreign Policy magazine to its list of top global thinkers in 2009 and 2010.
Nicholas started his talk by raising this question that why we as humans form social networks. Not only for sake of mating, people also befriending each other. Does natural selection have anything to do with humans' tendency to construct social networks? From the biology point of view, people with more friends are more likely to survive since they have stronger immune systems. Can someone extend this to social phenomena like happiness, cooperation, etc. ? To answer these questions, he conducted experiments on the field, which is the amazing part of his work. He demonstrated that there are three possible ways to explain the social clustering and similarity: induction, homophily, and context. For instance, one person buying the new iPhone may induce his or her friend to also buy the new iPhone, or two persons buy iPhone because both like it and same interests are the basis of their friendships. Another explanation is two related persons may buy the new iPhone because both of them are exposed to the Apple products more than other brands.
In one of Nicholas's experiments, he examined whether social characteristics spread across people and time. In his experiment subjects' cooperative actions are equally beneficial to all those with whom they interact. In this paper, he showed that when people can change their social ties, cooperation is maintained through the network rewiring. People prefer to break their ties with defectors and form connections with cooperators which acts as an incentive to cooperate. However, of the ties are fixed or change randomly, the cooperation decays over time. This conclusion prompts the fact that not only the sole connections matter, so does the network structure. This result also indicates another good point. Rigid ties are as harmful as random tie creation, so to maximize the cooperation the social rewiring should not be too difficult (rigid) or too easy (random - everyone can connect to everyone). An illustrative is the divorce; the divorce should not be impossible, but also not be too easy if the goal is to maximize the cooperation in the marriage. To emphasize the importance of the structure, Nicholas used the example of graphite and diamond. Both are made of carbon but arranged differently in the space which results in having different properties.
In another paper, he studied the human behavior under economic inequality. He and his colleagues found that when people are not aware of their neighbors' financial status, they all cooperate and interact better which at the end increases the overall wealth. However, when the significant financial difference is visible, the cooperation level decreases and the gap becomes wider than when the gap is invisible. He concludes that the payroll transparency policy should be applied with discretion. When the inequality is not high, the payroll transparency may increase the cooperation and overall wealth, while when the inequality is significant, transparency may magnify the inequality.
Nicholas's quantitative approach towards social phenomena is inspiring which potentially has policy-making and public health related inferences. If you would like to know more about his work, I recommend watching his TED Talk in 2010 on The Hidden Influence of Social Networks at the end of this post. You can also follow him on Twitter to know about his latest works!