The Origin of Peer Influence in Social Networks Recent empirical studies show that our choices and behaviors not only influence (and are influenced) by our friends but also their friends together with their friends’ friends (see figure): This concept, coined “the 3-degrees of influence”, attracted a lot of attention worldwide, not only giving rise to a very popular book (see ref1 below) and to Ted talks (TED2010 and TEDxSanDiego), but also it occupies, nowadays, a central concept in many procedures employed in web and social media applications. The “3-degrees of influence” were initially reported from an analysis conducted on the so-called Framingham Heart study database where the authors identified peer-influence correlations patterns for traits such as smoking habits, alcohol consumption, loneliness, obesity, cooperation or happiness. More importantly, these findings were later shown to transcend our modern social networks as further studies report similar patterns among hunter-gatherer societies in Tanzania. These extremely important findings imply rethinking the role played by the network of interactions that individuals use as a means to influence each-other. Clearly, the extent to which these “3 degrees of influence” are ubiquitous and pervasive, in the sense that they remain as such independent of what kind of information transmission process is at stake and of what type of network is wiring individuals, constitutes a natural and exceedingly important question. Researchers from the Portuguese group ATP and belonging to Universidade do Minho, Instituto Superior Técnico and Universidade de Aveiro, developed a study (see ref2 below) in which they try to answer the question above. To this end they used different models of information spreading and behavioral dynamics that have been developed in the physical, biological and social sciences over the last century, investigating what kinds of peer-influence patterns they observe, when populations of individuals interact along the links of the most pervasive network types identified during the last decades in the field of Network Science. The results of their computational approach explain why the patterns observed empirically are so similar. In fact, the authors show that the patterns observed empirically are but particular cases of a more universal behavior, in the sense that the peer-influence patterns remain essentially independent of the type of information, on how it spreads, and even of the type of social network that inter-connects individuals. Moreover, they find that the social networks leading to the stronger deviations from the “3 degrees of influence”, implying a larger degree of influence among peers are i) very sparse networks, that is, networks in which individuals have very few friends or contacts and ii) networks with high clustering, that is, networks in which, in most cases, two friends of any individual are also friends of each other. With this work the authors hope to help improving our understanding of the fundamental mechanisms responsible for the Peer Influence patterns found in Social Networks. Importantly, most of the networks linking medium to large communities have structures dictating that, to traverse the entire network, one needs to follow, on average a few links – in fact, the number of links is comparable to the ubiquitous “3 degrees of influence” we observe. In other words, in medium to large communities, everybody may influence and be influenced by almost everybody else. This is, to many, an astonishing and unexpected result, given the fact that, in all cases studied, information transmission involves only two individuals at a time. Not only our choices are strongly influenced by a large number of people we actually do not know, our influence on them goes well beyond what one would naively expect. References: [ref1] Nicholas A. Christakis, James H. Fowler, Connected: The Surprising Power of Our Social Networks and how They Shape Our Lives, Brown and Co (2009); (reprint edition, Back Bay Books 2011), [ref2] Flávio L. Pinheiro, Marta D. Santos, Francisco C. Santos & Jorge M. Pacheco, The Origin of Peer Influence in Social Networks, Physical Review Letters, in press (2014). For more information on the ATP-group see http://www.ciul.ul.pt/~ATP/, or contact Jorge M. Pacheco (email [email protected]), Flávio L. Pinheiro (email [email protected]), Francisco C. Santos (email [email protected]) or Marta D. Santos (email [email protected]). About the authors Flávio L. Pinheiro Marta D. Santos Francisco C. Santos Jorge M. Pacheco Flávio L. Pinheiro (Torres Vedras, 1987) has a BSc and MSc in Physics from the University of Lisbon and is currently a PhD student of the Physics Doctoral program (MAP-FIS) at the University of Minho. His interests range from the study of complex systems, behavioral evolution and cooperation. E-mail: [email protected] Web: http://www.ciul.ul.pt/~flavio/ Marta D. Santos (Lisbon, 1986) is currently a postdoctoral researcher at the complex systems group of the I3NUniversity of Aveiro. She is also a MSc. student of Science Communication at the New University of Lisbon, an area she is passionate about since her PhD years. Her research interests include complex networks, evolution of cooperation and epidemic models. E-mail: [email protected] Web: http://martadsants.weebly.com Francisco C. Santos (Lisbon, 1981) studied Physics at the University of Lisbon and earned his Ph.D. in Computer Science at the Université Libre de Bruxelles (2007). He is currently Assistant Professor at the Department of Computer Science of Instituto Superior Técnico of the University of Lisbon and member of INESC-ID. His interests span several aspects of complex adaptive systems, from the structure of social networks to human cooperation. E-mail: [email protected] Web: http://web.ist.utl.pt/franciscocsantos/ Jorge M. Pacheco (Oporto, 1958) is currently Professor of Mathematics at the Mathematics & Applications Department of the University of Minho and also a member of the Centre of Molecular and Environmental Biology. He is active in a variety of research topics, ranging from many-body physics to the mathematical description of evolutionary processes such as human cancer, evolution of cooperation, urban development & complexity and complex networks. E-mail: [email protected] Web: http://sites.google.com/site/jorgempacheco/