Planetary-Scale Views on a Large Instant-Messaging Network
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.
Social networks Communication networks Use demographics Large data Online communication.
Jure Leskovec Eric Horvitz
Carnegie Mellon University Microsoft Research
国际会议
第十七届国际万维网大会(the 17th International World Wide Web Conference)(WWW08)
北京
英文
2008-04-21（万方平台首次上网日期，不代表论文的发表时间）