“Distinguishing Influence Based Contagion from Homophily Driven Diffusion in Dynamic Networks” PNAS

Sinan Aral, Lev Muchnik andArun Sundararajan

ABSTRACT:

“Node characteristics and behaviors are often correlated with the structure of social networks over time. While evidence of this type of assortative mixing and temporal clustering of behaviors among linked nodes is used to support claims of peer influence and social contagion in networks, homophily may also explain such evidence. Here we develop a dynamic matched sample estimation framework to distinguish influence and homophily effects in dynamic networks, and we apply this framework to a global instant messaging network of 27.4 million users, using data on the day-by-day adoption of a mobile service application and users’ longitudinal behavioral, demographic, and geographic data. We find that previous methods overestimate peer influence in product adoption decisions in this network by 300–700%, and that homophily explains 50% of the perceived behavioral contagion. These findings and methods are essential to both our understanding of the mechanisms that drive contagions in networks and our knowledge of how to propagate or combat them in domains as diverse as epidemiology, marketing, development economics, and public health.”

Expertise Directory Development, Shared Task Interdependence, and Strength of Communication Network Ties as Multilevel Predictors of Expertise Exchange in Transactive Memory Work Groups

Yuan, Y. Connie,  Fulk, Janet,  Monge, Peter R.,  Contractor, Noshir

Communication Research 2010 37: 20-47

Just out in the new issue of Communication Research – an article combining social psychology and social network theory to explore transactive  memory processes.

Communication Research

Article abstract:
“Building on Kozlwoski and Klein’s emergence framework, this research developed and tested a set of multilevel hypotheses regarding individual and team transactive memory processes in work teams. Literature from social psychology suggested hypotheses on how shared task interdependence influences individual expertise exchange. Social network theory suggested hypotheses that individual expertise exchange is channeled according to communication tie strength. Using data collected from 218 individuals from 18 organizational teams, the proposed hypotheses were tested using hierarchical linear modeling techniques. The results showed that at the individual level the relationship between directory development and expertise exchange was mediated by communication tie strength and moderated by shared task interdependence.Team-level variables also were significantly related to individual-level outcomes such that individual expertise exchange happened more frequently in teams with well-developed team-level expertise directories, as well as with higher team communication tie strength and shared task interdependence.”

The  Facebook team shows commitment to academic research through a fellowship program for doctoral students.  This may turn into a particularly interesting project if  in addition to funding, the fellows also get access to the vast amount of data residing on the company’s servers.

Facebook Fellowship Program

Every day Facebook confronts the most complex technical problems and we believe that close relationships with the academy will enable us to address many of these problems at a fundamental level and solve them. As part of our ongoing commitment to academic relations, we are pleased to announce the creation of the Facebook Fellowship program to support graduate students in the 2010-2011 school year.

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Historical network analysis out of Stanford University maps the exchange of thousands of letters in the 18th century’s “Republic of Letters”:

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