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Semantic Web and Beyond #7: Social Networks and the Semantic Webby Peter Mika
Synopses & Reviews
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
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. It reveals how social network mining from the web plays an important role 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.
Whether we changed the Web or the Web has changed us, it is difficult to distill, even when equipped with the wisdom of hindsight. Social Networks and the Semantic Web 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 study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies. Social Networks and The Semantic Web is designed for researchers and advanced-level students of the semantic web and web services, information systems, social and information sciences. This book is useful for practitioners in industry as well.
Table of Contents
Foreword by Frank van Harmelen, author of the Semantic Web Primer.- Preface.- The Semantic Web and Social Networks.- The Semantic Web.- Social Network Analysis.- Semantic Technology for Social Network Analysis.- Electronic sources for network analysis.- Ontology-based Knowledge Representation.- Modelling and aggregating social network data.- Implementation of the methods.- Case Studies.- Evaluating electronic data extraction for network analysis.- Semantic-based Social Network Analysis in the sciences.- Ontologies are us: emergent semantics in folksonomy systems.- Conclusions.- Bibliography.- Index.
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