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Arun Chandrasekhar on mapping how information travels through social networks

Women in vibrant saris gather to talk at a corner of the old town of Kochi.

Women talking at a corner of the old town of Kochi (Cochin) in Kerala, India.

Nov 16 2015

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In development work, it is important to know which people have the ears of their neighbors. Whether the problem is enlisting cooperation in vaccination programs or introducing new agricultural methods, community members may not trust outside advice. The quickest route to success involves winning over those local residents who shape the attitudes of others. But how can these influential people be found? Development economists emphasize the key role of social networks—the web of relationships that defines community life. Finding a community’s most influential people may be a matter of identifying which personalities are central in these networks.

Arun Chandrasekhar, Stanford Assistant Professor of Economics and SCID Faculty Affiliate who specializes in social networks, has come up with an ingenious way of picking out the people at the center of community life. Traditionally, development workers map village networks by laboriously surveying every resident. But that is impractical in large-scale studies involving many communities. Instead of interviewing everyone in a village, Chandrasekhar talks with just a handful of people selected randomly. His most important question is basic: “Whose name do you hear most often?” In essence, he is asking who are the sources of gossip in a community. “We’re looking for people about whom there is a lot of chatter,” Chandrasekhar explains.

Chandrasekhar and fellow economists Abhijit Banerjee, Esther Duflo, and Matthew Jackson tested this idea in 210 Indian villages near the southern city of Bangalore. They set up a program to distribute free cell phones and then investigated which group was most effective in getting the word out: village leaders, residents chosen at random, or people the researchers identified as subjects of gossip. They got more than twice as many requests for phones when they spread news about the promotion through the gossip sources than through either of the other groups. “If you’re good at spreading information really widely, then many people have probably heard gossip about you,” Chandrasekhar says.

With support from SCID, Chandrasekhar is carrying out two other lines of research in India. The first involves mapping the structure of village social networks by finding people who have something unusual in common, like both knowing someone who went to jail. Sharing such unusual knowledge may mean that people are closely linked in the village’s network, providing one piece of the network’s overall structure. The second line of inquiry seeks to pinpoint what discourages members of social networks from sharing useful information, things like fear of the consequences of giving bad advice. Chandrasekhar’s findings will potentially help policymakers design development programs that take best possible advantage of village networks and sidestep obstacles to information sharing.