Social Networks and the Semantic Web offers valuable information to practitioners developing social-semantic software for the Web. It provides two major case studies. The first case study shows the possibilities of tracking a research community over the Web, combining the information obtained from the Web with other data sources and analyzing the results. Social network mining from the web plays an important role in this case study for obtaining large scale, dynamic network data beyond the possibilities of survey methods. The second case study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies.

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Klappentext

We are not just building the Web any more: we are on it. The latest set of applications have transformed the Web from a mere document collection into a social space: the new services developed under the banner of Web 2.0 cater to our needs of connecting through the medium and allow us to explicitly describe, maintain and develop our online self. At the same time, documents and other forms of content are not only up- and downloaded any more, but actively exchanged, filtered, organized and discussed in groups of all sizes. While the pace of change is dizzying, investigating this complex social-technological system is paramount to our ability of designing intelligent information systems that can guide us through the new online universe.

Social Networks and the Semantic Web combines the concepts and the methods of two fields of investigation, which together have the power to aid in the analysis of the social Web and the design of a new class of applications that combine human intelligence with machine processing. Social Network Analysis and the emerging Semantic Web are also the fields that stand to gain most from the new Web in achieving their full potential. On the one hand, the social Web delivers social network data at an extraordinary scale, with a dynamics and precision that has been outside of reach for more traditional methods of observing social structure and behavior. In realizing this potential, the technology of the Semantic Web provides the key in aggregating information across heterogeneous sources. The Semantic Web itself benefits by incorporating user-generated metadata and other clues left behind by users.

Social Networks and the Semantic Web is designed for practitioners and researchers in industry, as well as graduate-level students in Computer Science within the Semantic Web field, and Social Science with an interest in working with electronic data and observing online social networks. This book also supplies developers of social-semantic applications with an understanding of the key concepts and methods of both fields and describes real-world applications incorporating social and semantic metadata.

Foreword by Frank van Harmelen, author of the Semantic Web Primer

Zusammenfassung
Science is like a tree: contrary to popular belief, both trees and science grow at their edges, not at their core. For science, this means that most of the fruitful and exciting developments are not happening at the core of established ?elds, but are instead happening at the boundaries between such ?elds. This has been particularly true for Computer Science. The most interesting database developments don't happen inside the Database community, but rather where databases hit Biology. Similarly, the most interesting developments in Ar- ?cial Intelligence in recent years have happened where AI met the Web. Theyoung?eldofSemanticWebresearchhasbeenoneoftheresultsofanumber of different sub?elds of Computer Science being exposed to the challenges of the Web: databases, computational linguistics, knowledge representation, knowled- based systems and service-oriented computing are just some of the sub?elds that are all making contributions to the Semantic Web vision, namely a Web that consists not only of linksbetween web-pagesfull of picturesand text, but of a Semantic Web that consists of links between computer-interpretable data. Such a Semantic Web would make it possible to query and reason over integrated data-sets consisting of separate pieces of information that were never intended to be linked together, but that can nevertheless be fruitfully combined and integrated, sometimes even by a third party who neither wrote nor ownsany of the original piecesof data (just as is possible with web-pages on the current Web).

Inhalt
to the Semantic Web and Social Networks.- The Semantic Web.- Social Network Analysis.- Web data and semantics in social network applications.- Electronic sources for network analysis.- Knowledge Representation on the Semantic Web.- Modelling and aggregating social network data.- Developing social-semantic applications.- Case studies.- Evaluation of web-based social network extraction.- Semantic-based Social Network Analysis in the sciences.- Ontologies are us: emergent semantics in folksonomy systems.- Conclusions.- The perfect storm.