Abstract
We present a study of anonymized data capturing a month of high-level communi-
cation activities within the whole of the Microsoft Messenger instant-messaging system.
We examine characteristics and patterns that emerge from the collective dynamics of
large numbers of people, rather than the actions and characteristics of individuals.
The dataset contains summary properties of 30 billion conversations among 240 mil-
lion people. From the data, we construct a communication graph with 180 million
nodes and 1.3 billion undirected 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
investigate 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.
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