Friends and neighbors on the Web Export

@article{citeulike:882572, abstract = {The Internet has become a rich and large repository of information about us as individuals. Anything from 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. In this paper we devise techniques and tools to mine this information in order to extract social networks and the exogenous factors underlying the networks' structure. In an analysis of two data sets, from Stanford University and the Massachusetts Institute of Technology (MIT), we show that some factors are better indicators of social connections than others, and that these indicators vary between user populations. Our techniques provide potential applications in automatically inferring real world connections and discovering, labeling, and characterizing communities.}, author = {Adamic, L. A. and Adar, E.}, citeulike-article-id = {882572}, citeulike-linkout-0 = {http://www.ingentaconnect.com/content/els/03788733/2003/00000025/00000003/art00009}, journal = {Social Networks}, keywords = {social-networks, sota}, month = {July}, number = {3}, pages = {211--230}, posted-at = {2006-10-03 12:48:28}, priority = {5}, publisher = {Elsevier}, title = {Friends and neighbors on the Web}, url = {http://www.ingentaconnect.com/content/els/03788733/2003/00000025/00000003/art00009}, volume = {25}, year = {2003} }

TY - JOUR ID - citeulike:882572 L3 - citeulike-article-id:882572 N2 - The Internet has become a rich and large repository of information about us as individuals. Anything from 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. In this paper we devise techniques and tools to mine this information in order to extract social networks and the exogenous factors underlying the networks' structure. In an analysis of two data sets, from Stanford University and the Massachusetts Institute of Technology (MIT), we show that some factors are better indicators of social connections than others, and that these indicators vary between user populations. Our techniques provide potential applications in automatically inferring real world connections and discovering, labeling, and characterizing communities. IS - 3 JF - Social Networks EP - 230 TI - Friends and neighbors on the Web PB - Elsevier VL - 25 SP - 211 KW - social-networks KW - sota AU - Adamic, LA AU - Adar, E PY - 2003/07// UR - http://www.ingentaconnect.com/content/els/03788733/2003/00000025/00000003/art00009 ER -