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Understanding Online Communities by Using Semantic Web Technologies
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Author(s): Alexandre Passant (National University of Ireland-Galway, Ireland), Sheila Kinsella (National University of Ireland-Galway, Ireland), Uldis Bojars (National University of Ireland-Galway, Ireland), John G. Breslin (National University of Ireland-Galway, Ireland)and Stefan Decker (National University of Ireland-Galway, Ireland)
Copyright: 2011
Pages: 28
Source title:
Handbook of Research on Methods and Techniques for Studying Virtual Communities: Paradigms and Phenomena
Source Author(s)/Editor(s): Ben Kei Daniel (University of Saskatchewan, Canada)
DOI: 10.4018/978-1-60960-040-2.ch026
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Abstract
During the last few years, the Web that we used to know as a read-only medium shifted to a read-write Web, often known as Web 2.0 or the Social Web, in which people interact, share and build content collaboratively within online communities. In order to clearly understand how these online communities are formed, evolve, share and produce content, a first requirement is to gather related data. In this chapter, we give an overview of how Semantic Web technologies can be used to provide a unified layer of representation for Social Web data in an open and machine-readable manner thanks to common models and shared semantics, facilitating data gathering and analysis. Through a comprehensive state of the art review, we describe the various models that can be applied to online communities and give an overview of some of the new possibilities offered by such a layer in terms of data querying and community analysis.
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