Year: 2008
Type: conference-paper
Abstract: Social networks are of interest to researchers in part because they are thought to mediate the flow of information in communities and organizations. Here we study the temporal dynamics of communication using on-line data, including e-mail communication among the faculty and staff of a large university over a two-year period. We formulate a temporal notion of "distance" in the underlying social network by measuring the minimum time required for information to spread from one node to another - a concept that draws on the notion of vector-clocks from the study of distributed computing systems. We find that such temporal measures provide structural insights that are not apparent from analyses of the pure social network topology. In particular, we define the network backbone to be the subgraph consisting of edges on which information has the potential to flow the quickest. We find that the backbone is a sparse graph with a concentration of both highly embedded edges and long-range bridges - a finding that sheds new light on the relationship between tie strength and connectivity in social networks.
Authors: Gueorgi Kossinets, Jon Kleinberg, Duncan Watts
Institution: Cornell University
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Awards: ITR: Networks of Strategic Agents: Theory and Algorithms, EITM: The Structure, Evolution, and Function of Large-Scale Social Networks: Theory, Data, and Experiment., Graph-based Approaches to Text Processing, Very Large Semi-Structured Datasets for Social Science Research, Petabyte Storage Services For Data-Driven Science
OpenAlex ID: W2125349172