PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Planetary-Scale Views on a Large Instant-Messaging Network
Jure Leskovec and Eric Horvitz
In: WWW 2008, April 21 - April 25 2008, Beijing, China.

Abstract

We present a study of anonymized data capturing a month of high-level communication activities within the whole of the Microsoft Messenger instant-messaging system. We ex- amine characteristics and patterns that emerge from the col- lective dynamics of large numbers of people, rather than the actions and characteristics of individuals. The dataset con- tains summary properties of 30 billion conversations among 240 million people. From the data, we construct a commu- nication graph with 180 million nodes and 1.3 billion undi- rected edges, creating the largest social network constructed and analyzed to date. We report on multiple aspects of the dataset and synthesized graph. We find that the graph is well-connected and robust to node removal. We inves- tigate on a planetary-scale the oft-cited report that people are separated by “six degrees of separation” and find that the average path length among Messenger users is 6.6. We also find that people tend to communicate more with each other when they have similar age, language, and location, and that cross-gender conversations are both more frequent and of longer duration than conversations with the same gender.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:5132
Deposited By:Jan Rupnik
Deposited On:24 March 2009