%0 Book Section %1 statphys23_0718 %A Lee, S.H. %A Kim, P.J. %A Ahn, Y.Y. %A Jeong, H. %B Abstract Book of the XXIII IUPAP International Conference on Statistical Physics %C Genova, Italy %D 2007 %E Pietronero, Luciano %E Loreto, Vittorio %E Zapperi, Stefano %K complex engine network search social statphys23 topic-11 weighted %T Social network analysis based on WWW search engine %U http://st23.statphys23.org/webservices/abstract/preview_pop.php?ID_PAPER=718 %X Recently, massive digital records have made it possible to analyze a huge amount of data in social sciences, one of which is social network theory. We investigate social networks between people by extracting information on the World Wide Web. Using famous search engines such as Google, we construct weighted social networks where the nodes are the names of people and the weight of each link is assigned as the number of web pages including both of the names attached to the link. The weight distribution is found to be quite broad with the heavy-tail. The strength of a node, defined as the sum of weights over the node, is strongly correlated with the number of web pages including the single node. Furthermore, we suggest the quantity, called the effective degree, characterizing the homogeneity (or heterogeneity) of weight distribution for each node in the weighted network. Another way to quantify the importance of each node, based on the effective degree, is also introduced.

@incollection{statphys23_0718, abstract = {Recently, massive digital records have made it possible to analyze a huge amount of data in social sciences, one of which is social network theory. We investigate social networks between people by extracting information on the World Wide Web. Using famous search engines such as Google, we construct weighted social networks where the nodes are the names of people and the weight of each link is assigned as the number of web pages including both of the names attached to the link. The weight distribution is found to be quite broad with the heavy-tail. The strength of a node, defined as the sum of weights over the node, is strongly correlated with the number of web pages including the single node. Furthermore, we suggest the quantity, called the effective degree, characterizing the homogeneity (or heterogeneity) of weight distribution for each node in the weighted network. Another way to quantify the importance of each node, based on the effective degree, is also introduced.}, added-at = {2007-06-20T10:16:09.000+0200}, address = {Genova, Italy}, author = {Lee, S.H. and Kim, P.J. and Ahn, Y.Y. and Jeong, H.}, biburl = {https://www.bibsonomy.org/bibtex/2a4d441aefbc16af427dfa1a943711f4e/statphys23}, booktitle = {Abstract Book of the XXIII IUPAP International Conference on Statistical Physics}, editor = {Pietronero, Luciano and Loreto, Vittorio and Zapperi, Stefano}, interhash = {138d5f5f98289d0797d302c2b8ad31e2}, intrahash = {a4d441aefbc16af427dfa1a943711f4e}, keywords = {complex engine network search social statphys23 topic-11 weighted}, month = {9-13 July}, timestamp = {2007-06-20T10:16:27.000+0200}, title = {Social network analysis based on WWW search engine}, url = {http://st23.statphys23.org/webservices/abstract/preview_pop.php?ID_PAPER=718}, year = 2007 }