Detecting and Understanding Web communities

Web communities comprising of documents and/or users activities have beenformed and are continuously expanding and transforming as Web users role shiftsfrom typical navigations to content managing and regulating. Defining, deriving andexploiting communities is not a trivial task since several parameters (large-scale,complexity, evolving information etc) are involved. This paper aims at providinganswers for crucial questions raised about communities emerging in the Web and itsummarizes different community definitions such that then, the problem ofcommunity detection (which is well matured and researched in the past) isunderstood. The paper emphasizes and discusses the most important methodologiesand techniques which deal with large populations of Web documents participatingin vast hyperlinked networks, or networks formed from crawling (part of) the weband more recently, networks reflecting the social relations and/or interactions amongpeople. It is important to understand and categorize community identification effortsby taking into account that different levels of granularity and different views areoften used for community identification. The emphasis is on the intuition behind allthese methodologies and implementations, and on their practical impact for tasks ofrecommendation, searching, content outsourcing, etc.