Complexity and Social Networks Blog

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16 November 2009

Cambridge Colloquium on Complexity and Social Networks: Michael Macy on "The Length of Weak Ties"

A short schedule for CCCSN this term, with Michael Macy on November 23 and Carter Butts on December 10. The details on Macy:

Michael Macy (Cornell)

The Length of Weak Ties

November 23, 12-1:30pm
440 Huntington Ave. ~ 366 West Village H

Granovetter's theory of "the strength of weak ties" is one of the most-cited social theories in network science and an important precursor for Watts' and Strogatz' discovery of small world networks. The "strength" is that information about economic opportunities is more likely to come from socially distant acquaintances than close friends. Until recently, however, the structure and strength of social ties has been almost impossible to measure at the societal level. We test predictions of this theory by combining the most complete record of a national communication network studied to date with data on the socio-economic well-being of communities and the purchasing behavior of individuals. We show for the first time that the diversity of individuals' ties has a strong positive correlation with the social and economic rank of the community (R2=.78). Moreover, contrary to theoretical predictions, clustered relations were no stronger than ties that bridge between clusters and yet were more effective as conduits of peer influence. We speculate that ties within clusters are mainly friendship-oriented, while those between clusters are mainly task-oriented.

Three other talks of interest this coming week:

The College of Computer and Information Science presents a Colloquium by:

Madhav Marathe (Virginia Tech)
Computational Network and Social Science: Implications for Public Policy

Date: Wednesday, November 18
Time: 2:00pm
Place: 366 West Village H

Title:

Abstract:
Complex Networks are pervasive in our society. Realistic biological, information, social and technical networks share a number of unique features that distinguish them from physical networks. Examples of such features include: irregularity, time-varying structure, heterogeneity among individual components and selfish/cooperative
game-like behavior by individual components. Furthermore, the network structure, the dynamical process on the network and the behavior of constituent agents co-evolve over time. The size and heterogeneity of these networks, their co-evolving nature and the technical difficulties in applying dimension reduction techniques commonly used to analyze physical systems makes the task to understanding and reasoning about these networks even more challenging.

Recent quantitative changes in high performance and pervasive computing including faster machines, distributed sensors and service-oriented software have created new opportunities for collecting, integrating, analyzing and accessing information related to such large complex networks. The advances in network and information science that build on this new capability provide entirely new ways for reasoning and controlling these networks. Together, they enhance our ability to formulate, analyze and realize novel public policies pertaining to these complex networks.

Over the last 15 years, our group has established a theory based program for modeling, simulation and associated decision support tools for understanding large complex network. Complementing this is a program to develop a scalable service delivery framework, that provides policy analysts and scientists seamless access to the modeling
environment. After a brief overview, I will describe our approach within the context of a specific application: development of modeling and decision support environments to study epidemics in co-evolving social and wireless networks. Understanding these
epidemiological processes is of immense societal importance. Additionally they serve as excellent "model organisms" for developing a theory of co-evolving complex networks. Individual and collective behavioral adaptation is critical in these systems and will be highlighted via illustrative case studies.

Nov 18th, 3:30-5:00 pm
Harvard Jason Greenberg, MIT
Lifeblood or Liability?: Schumpeter, Stinchombe, and the Double-edged Sword of Strangers or Strong ties in the Startup Process
1550 William James Hall.

Who should you start a business with, individuals you trust such as family members or friends or strangers who are more likely able to provide access to distinct resources? In one of the most influential arguments in organizational sociology Arthur Stinchcombe argued that new as opposed to old organizations are more likely to die because of a "liability of newness." The general thesis has received empirical support. However, Stinchcombe identified four mechanisms that individually and collectively compose the liability. One of the liabilities he identified holds that new organizations are more likely to die because they must rely upon relations among strangers, and strangers are less likely to trust each other. Trust, in turn, is an essential ingredient in economic transactions that entail risk and uncertainty, which are central elements of any startup. This "liability of strangers" mechanism has not been evaluated empirically in startups. On the other hand, research suggests that strangers are particularly well suited to act as bridging ties that afford advantages in the startup process by offering access to diverse information about market opportunities and distinct resources. This social structural mechanism is consistent with Schumpeter's view of entrepreneurship as novel combination and Simmel's theorization of the social position of stranger. This paper assesses whether including strangers or strong ties (e.g., family, friends) on a founding team is net positive or negative in terms of predicting the fraction of business-relevant milestones achieved, dissolving the venture, or achieving viability. Results consistently show that starting a business with friends from outside work is associated with negative outcomes, whereas starting a business with friends from work is associated with positive outcomes. There also does not appear to be a liability of strangers. In point of fact, founding teams in knowledge or research intensive firms that include stranger dyads in the founding team are more likely to accomplish business-relevant milestones.

Nathan Eagle, (Santa Fe Institute & MIT)
Big Data, Global Development, and Complex Social Systems
Friday, November 20th at 2:30 PM
440 Huntington Ave. ~ 366 West Village H
Boston, MA 02115

Petabytes of data about human movements, transactions, and communication patterns are continuously being generated by everyday technologies such as mobile phones and credit cards. This unprecedented volume of information facilitates a novel set of research questions applicable to a wide range of development issues. In collaboration with the mobile phone, internet, and credit card industries, my colleagues and I are aggregating and analyzing behavioral data from over 250 million people from North and South America, Europe, Asia and Africa. I will discuss a selection of projects arising from these collaborations that involve inferring behavioral dynamics on a broad spectrum of scales; from risky behavior in a group of MIT freshman to population-level behavioral signatures, including cholera outbreaks in Rwanda and wealth in the UK. Access to the movement patterns of the majority of mobile phones in East Africa also facilitates realistic models of disease transmission as well as slum formations. This vast volume of data requires new analytical tools - we are developing a range of large-scale network analysis and machine learning algorithms that we hope will provide deeper insight into human behavior. However, ultimately our goal is to determine how we can use these insights to actively improve the lives of the billions of people who generate this data and the societies in which they live.

Posted by David Lazer at November 16, 2009 5:26 PM

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