Economic Influence in Massive Online Social Networks

1 Introduction We use an unprecedented data set to examine the extent to which networked social relationships between consumers explain, and in fact influence, patterns of user behavior, e-commerce service adoption, online demand and ultimately revenue generation. Our data include a global instant messaging (IM) network of 27 million users from one of the largest online portals in the world, combined with a) detailed data on the day-by-day adoption of a mobile service application launched by the portal in June 2007, and b) detailed and precise data on nearly all e-commerce actions taken by the same users on the portal's various websites. The data contain daily IM message traffic for each of the 27 million users, the adoption date and per day page views of users of the mobile service application, per-day page views of different types of portal content (for example, sports, weather, and finance) for all users, and detailed geographic and demographic data. It took two and a half years to negotiate access to the data, which we intend to make public for validation, verification and continued research. These data will allow researchers to explore many topics, but our primary goal is to analytically model influence in networked adoption processes and to econometrically distinguish influence from selection in the relationship between consumers' social relationships and their online decisions. Simply stated, the research question is: to what extent do networked relationships influence consumers' economic choices, creating systematic population level patterns in product demand and other user behaviors? Our findings could have dramatic implications not only for e-commerce, but also for our collective understanding of how networks influence outcomes of social and economic significance. In their most immediate application, our findings inform research in online marketing, consumer demand, organizational economics, and the diffusion of information and social influence in large populations. There has been a recent explosion in research about networks of various kinds. Our project and others like it are of unique interest to WCBI because they combine the analysis of massive electronic networked data sets with questions relating to economic and business impact. Scholars across disciplines as diverse as economics, sociology, computer science and physics have examined the persistent structural properties of networks (Newman 2003) how they form, evolve and dissolve (Price 1976, Barabasi and Albert 1999), and how they affect socioeconomic outcomes like information worker productivity (Aral et al. 2006, 2007, Aral and Van Alstyne 2007) and …