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Lada A. Adamic and Eytan Adar
First Monday, 8(6), 2003.


The Internet has become a rich and large repository of information about individuals. The links and text on a user's homepage to the mailing lists the user subscribes to are reflections of social interactions a user has in the real world. We devise techniques to mine this information in order to predict relationships between individuals. Further we show that some pieces of information are better indicators of social connections than others. The high quality information we discover provides a glimpse into the social life of two communities and has potential applications in automatically inferring real-world connections and discovering and labeling communities.

Pre-print last modified: 03/02/01
Full paper: PDF (03/02/01 version)

Supplementary material:
Frequency of Friendship Predictors (HTML)
Online demonstration of the Stanford Social Web.

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