Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials

74 Pages Posted: 10 Jun 2014 Last revised: 21 Mar 2018

Abhijit V. Banerjee

Massachusetts Institute of Technology (MIT) - Department of Economics

Arun G. Chandrasekhar

Stanford University - Department of Economics

Esther Duflo

Massachusetts Institute of Technology (MIT) - Department of Economics; Abdul Latif Jameel Poverty Action Lab (J-PAL); National Bureau of Economic Research (NBER); Centre for Economic Policy Research (CEPR); Bureau for Research and Economic Analysis of Development (BREAD)

Matthew O. Jackson

Stanford University - Department of Economics; Santa Fe Institute; Canadian Institute for Advanced Research (CIFAR)

Multiple version iconThere are 3 versions of this paper

Date Written: May 6, 2017

Abstract

Is it possible to identify individuals who are highly central in a community without gathering any network information, simply by asking a few people to tell us whom we seed a information with if we want it to spread widely in the community? If we use people's nominees as seeds for a diffusion process, will it be successful? In a first "proof of concept" RCT run in 213 villages in Karnataka, India, information about opportunities to get a free cell phone or money diffused more widely when it was initially given to people nominated by others than when it was given to randomly selected people, or village elders. In a second large scale policy RCT in 517 villages in Haryana, India, the monthly number of vaccinations increased by 22% in randomly selected villages in which nominees were given information about about upcoming monthly vaccination camps and asked to spread it, than when randomly selected villagers were given the same information. After presenting the results from these RCTs, we show via a simple model how members of a community can just by tracking gossip about others, identify highly central individuals in their network. Asking villagers in rural Indian villages to name good seeds for diffusion, we find that they accurately nominate those who are central according to a measure tailored for diffusion -- not just those with many friends or in powerful positions.

Keywords: Centrality, Gossip, Networks, Diffusion, Influence, Social Learning

JEL Classification: D85, D13, L14, O12, Z13

Suggested Citation

Banerjee, Abhijit V. and Chandrasekhar, Arun G. and Duflo, Esther and Jackson, Matthew O., Using Gossips to Spread Information: Theory and Evidence from Two Randomized Controlled Trials (May 6, 2017). MIT Department of Economics Working Paper No. 14-15. Available at SSRN: https://ssrn.com/abstract=2425379 or http://dx.doi.org/10.2139/ssrn.2425379

Abhijit V. Banerjee

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

50 Memorial Drive
Room E52-252D
Cambridge, MA 02142
United States
617-253-8855 (Phone)
617-253-6915 (Fax)

Arun G. Chandrasekhar

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States

Esther Duflo

Massachusetts Institute of Technology (MIT) - Department of Economics ( email )

50 Memorial Drive
Room E52-544
Cambridge, MA 02139
United States
617-258-7013 (Phone)
617-253-6915 (Fax)

Abdul Latif Jameel Poverty Action Lab (J-PAL) ( email )

Cambridge, MA
United States

HOME PAGE: http://www.povertyactionlab.org/

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Centre for Economic Policy Research (CEPR)

77 Bastwick Street
London, EC1V 3PZ
United Kingdom

Bureau for Research and Economic Analysis of Development (BREAD) ( email )

Duke University
Durham, NC 90097
United States

Matthew O. Jackson (Contact Author)

Stanford University - Department of Economics ( email )

Landau Economics Building
579 Serra Mall
Stanford, CA 94305-6072
United States
1-650-723-3544 (Phone)

HOME PAGE: http://www.stanford.edu/~jacksonm

Santa Fe Institute

1399 Hyde Park Road
Santa Fe, NM 87501
United States

Canadian Institute for Advanced Research (CIFAR) ( email )

180 Dundas Street West, Suite 1400
Toronto, Ontario
Canada

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