In this paper the utility of using the Self Organizing Maps (SOM), in conjunction with U-matrix, to visualize the evolution of a social network community formed by a set of blogs is shown. Weblogs are dynamic websites updated via easy-to-use content management systems whose links tend to mirror or in some cases establish new types of social relations, thereby creating a social network. Analyzing the evolution of this network allows the discovery of emerging social structures and their trends in growth. Here we apply this method to Blogalia, a blog hosting site from which we have a complete set of data. The proposed procedure not only gives some insight on how communities form and evolve, but would also enable to predict the future paths that their members will take.
%0 Book Section
%1 PrietoMereloprietoTricas07
%A Prieto, Beatriz
%A Merelo, JuanJ
%A Prieto, Alberto
%A Tricas, Fernando
%B Computational and Ambient Intelligence
%D 2007
%E Sandoval, Francisco
%E Prieto, Alberto
%E Cabestany, Joan
%E Gra\ na, Manuel
%I Springer Berlin Heidelberg
%J Computational and Ambient Intelligence
%K citas, citeulike kohonen, referencias, som
%P 911--918
%R 10.1007/978-3-540-73007-1_110
%T Analyzing a Web-Based Social Network Using Kohonen's SOM
%U http://dx.doi.org/10.1007/978-3-540-73007-1_110
%V 4507
%X In this paper the utility of using the Self Organizing Maps (SOM), in conjunction with U-matrix, to visualize the evolution of a social network community formed by a set of blogs is shown. Weblogs are dynamic websites updated via easy-to-use content management systems whose links tend to mirror or in some cases establish new types of social relations, thereby creating a social network. Analyzing the evolution of this network allows the discovery of emerging social structures and their trends in growth. Here we apply this method to Blogalia, a blog hosting site from which we have a complete set of data. The proposed procedure not only gives some insight on how communities form and evolve, but would also enable to predict the future paths that their members will take.
@incollection{PrietoMereloprietoTricas07,
abstract = {{In this paper the utility of using the Self Organizing Maps (SOM), in conjunction with U-matrix, to visualize the evolution of a social network community formed by a set of blogs is shown. Weblogs are dynamic websites updated via easy-to-use content management systems whose links tend to mirror or in some cases establish new types of social relations, thereby creating a social network. Analyzing the evolution of this network allows the discovery of emerging social structures and their trends in growth. Here we apply this method to Blogalia, a blog hosting site from which we have a complete set of data. The proposed procedure not only gives some insight on how communities form and evolve, but would also enable to predict the future paths that their members will take.}},
added-at = {2017-09-08T10:52:59.000+0200},
author = {Prieto, Beatriz and Merelo, JuanJ and Prieto, Alberto and Tricas, Fernando},
biburl = {https://www.bibsonomy.org/bibtex/216e73b56efa8433d68763e8305e8726c/fernand0},
booktitle = {Computational and Ambient Intelligence},
citeulike-article-id = {3243020},
citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-540-73007-1_110},
citeulike-linkout-1 = {http://link.springer.com/chapter/10.1007/978-3-540-73007-1_110},
doi = {10.1007/978-3-540-73007-1_110},
editor = {Sandoval, Francisco and Prieto, Alberto and Cabestany, Joan and Gra\ {n}a, Manuel},
interhash = {d4c42e3dc3b95cc6abb8208923718f53},
intrahash = {16e73b56efa8433d68763e8305e8726c},
journal = {Computational and Ambient Intelligence},
keywords = {citas, citeulike kohonen, referencias, som},
pages = {911--918},
posted-at = {2013-06-28 17:42:37},
priority = {2},
publisher = {Springer Berlin Heidelberg},
series = {Lecture Notes in Computer Science},
timestamp = {2017-09-08T10:53:23.000+0200},
title = {{Analyzing a Web-Based Social Network Using Kohonen's SOM}},
url = {http://dx.doi.org/10.1007/978-3-540-73007-1_110},
volume = 4507,
year = 2007
}