Clearly, the web is both a technological and social phenomenon. Consequently, only a determined interdisciplinary effort will be successful in forging a deeper understanding of its structure and function. A key focus will be to study the formation and evolution of communities within the web and other technological systems. We intend to use the knowledge of such communities to design better techniques for exploring those networks and retrieving specific information..  The currently most successful strategy for web search relies on the Page Rank algorithm which navigates the web by exploiting only its most basic link structure – how pages link to one another via hypertext links. But web documents (texts, images, media files and data) are also connected to each other by virtue of their membership in larger communities. Such communities – evident as clusters of densely interlinked pages – often have a thematic meaning based on some shared property. By focusing on the identification of such communities, we believe it will be possible to provide a thematic division of the web that will facilitate web crawling and information retrieval. Doing so will require an effective combination of  the mathematics of graph theory and computer science with the traditional behavioural perspective of the social sciences, while also bringing in  the modern techniques of statistical physics which are specifically suited for dealing with large systems such as the World Wide Web.

This section is edited by Claudio Castellano.