Year: 2003
Type: preprint
Abstract: Websites of a particular class form increasingly complex networks, and new tools are needed to map and understand them. A way of visualizing this complex network is by mapping it. A map highlights which members of the community have similar interests, and reveals the underlying social network. In this paper, we will map a network of websites using Kohonen's self-organizing map (SOM), a neural-net like method generally used for clustering and visualization of complex data sets. The set of websites considered has been the Blogalia weblog hosting site (based at http://www.blogalia.com/), a thriving community of around 200 members, created in January 2002. In this paper we show how SOM discovers interesting community features, its relation with other community-discovering algorithms, and the way it highlights the set of communities formed over the network.
Source: arXiv (Cornell University)
Authors: Merelo-Guervos, Juan-J., Prieto, Beatriz, Rateb, Fatima, Tricas, Fernando
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1672496925