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Reviewer: Maria Bielikova

Social aspects of the Web are becoming increasingly important for our effective discovery and use of information and knowledge on the Internet. Considering all of the people who look up information on the Web and all of the individual users or communities that use Web-based applications, we can confidently state that the Web is going through a process of changing into a social Web. Mika addresses, in this book, these emerging social issues. He is also concerned with the connection between the social aspects of the Web and the semantic Web vision that is directed toward automatic reasoning of information presented on the Web, using the semantics of data represented in machine-readable form. Social networks and the semantic Web are active research areas that overlap several fields of computer science, artificial intelligence, software engineering, and social and information sciences. Mika is concerned with conceptual analyses of particular issues related to social networks, the semantic Web, and their mutual interconnection, as well as technological aspects presented as examples of software design and engineering. The book is well written and contains many discussions and real-life analogies used to explain why the Web needs an extension. It presents two major case studies that demonstrate the importance of the social aspects of the Web and the need for explicit expression of the semantics of Web content. The focus is on the methods presented rather than on particular results, as the methods are more generally applicable. The first case study shows the possibilities of tracking a research community over the Web, using information obtained from different data sources, such as publications or emails. The second case study deals with popular tagging systems known as folksonomies. The book is divided into four parts and ten chapters. Each chapter contains a discussion where Mika presents various analyses and a summary of the most important aspects of the particular chapter. Part 1 presents an introduction to the semantic Web and social networks, in two separate chapters; therefore, previous knowledge of social networks and the semantic Web is not necessary for reading this book. Part 2 is devoted to selected issues related to Web data and semantics in social networking applications. Chapter 3 shows possibilities for collecting social network data from Internet sources, such as electronic discussion networks, blogs, and online communities. Chapters 4 and 5 present semantic-based representations of data as the basis for developing social-semantic applications?the topic of the next chapter. Chapter 6 presents the general design of semantic Web applications, followed by a brief introduction of three typical semantic Web applications: Sesame, Elmo, and the Graph utility. The design of two systems developed by Mika?Flink and openacademia?is also discussed. Part 3 discusses two case studies, and presents a tripartite model of ontologies, together with case studies on its usage. In the last part, "Conclusions," Mika looks back and tells the story of one social network (the Katrina PeopleFinder Project, developed as a volunteer effort to help find people after Hurricane Katrina in August 2005), and then looks ahead at the challenges of social networks and the semantic Web in the context of artificial networks (systems such as Second Life). This book advances concepts of social networks analysis and the semantic Web. It represents mostly the results of Mika's own research, and contains many ideas that could be an inspiration for further research. I recommend the book to researchers in the field of information processing on the Web, and for graduate or postgraduate seminars in informatics and information and social sciences. Online Computing Reviews Service

Reviewer: Jeffrey B. Putnam

The study of social networks has been around for a while now, but the application of graph theory and computer methods has given a more analytic face to the topic. This promises to be a fascinating area of research in the future, as these techniques are used to analyze everything from how communities of people are built to how organizations are run. In particular, the Internet and Web provide sources of data that can be used for the analysis of social networks. Consider all the possibilities: email, chat systems, online games, and links from Web pages. They all reflect in some way the social interactions of people, and the emergence, growth, and sometimes decline of communities. And, of course, there are the specifically social Web sites, such as MySpace and Facebook. The semantic Web is an emerging set of technologies intended to provide automatic (machine) interpretation of information and derive meaning from that. The semantic Web is often built on ontologies-descriptions of something (or of related things) using an ontology representation language. Ontologies are usually built of triples, essentially subject-connector-object groupings. For example, a simple triple, in no specific ontology markup, might be "Saturn-rdf:type-planet," meaning that Saturn is a planet. Since ontologies are intended to be comprehensive, the term planet itself is likely to be described somewhere in an ontology, to which the ontology describing Saturn may link; "rdf:type" is a defined connector in the resource description framework (RDF) ontology description notation. Semantic Web technologies seem a natural fit for studying social networks. Since the ontologies are both descriptive and flexible, they can be used to describe new kinds of relationships as they are discovered, and their description serves both to define the new kind of relationship and provide a way for algorithms to explore it. This book is about the intersection of semantic Web technologies and social networks. It provides an overview of both topics, and detailed information about how ontologies are represented and how social network data is modeled. It then provides three chapters on extracting social network information from the Web; on modeling social networks in scientific communities, particularly in the community of scientists focused on the semantic Web; and on folksonomies. It finishes with a chapter covering the emergence of Web-based systems for locating people after hurricane Katrina. The strongest parts of the book are its overviews of social networks and the semantic Web. The sections on social networking are very good indeed, and might well serve to draw people from divergent disciplines into a fascinating field of research. The overview of the semantic Web and of the various ontology representation languages is also good, but the subject is very complex and difficult, and the reader will need to look elsewhere for enough coverage to answer anything but the simplest questions. Later sections are weaker. The chapters seem rushed, and are not well edited. For example, in chapter 7, on Web-based social network analysis, Figure 7.3 is almost unreadable, and the x and y axes have no meaningful explanations. Figure 7.1 shows that one individual seems to have produced more than a million Web pages-this is a remarkable fact, as it would mean that one person has produced 160 Web pages a day, every day, since 1990. Other figures are many pages away from their references (in one case, ten pages), or are hard to read. One figure purports to show DARPA Agent Markup Language for Services (DAML-S) researchers forming a cluster away from the core researcher in the area, but how it shows that is beyond my ken. The section on social networks in the semantic Web community seems to be more of a discussion of that community than a serious analysis of the social networks involved. In a few places, Mika is crusading against Extensible Markup Language (XML) in favor of RDF or other ontology representations. There is much to be said about XML's limitations and problems-and many who say it-but RDF, XML, and other forms of data markup, such as the tuples in a relational database, do not necessarily compete to solve the same problems. In particular, in the discussion on the people finder system developed in the aftermath of hurricane Katrina, the inflexibility of a quickly developed XML schema is pointed out as a weakness of the representation. It is far from clear how the flexibility of RDF, and the tools available to use it at that point, would have led to a better result. While this is likely to change with the emergence of new tools, many of which are mentioned in the book, it seems, at this point, that each of the various technologies has specific strengths and weaknesses, and no one will entirely replace the others. The focus should be on helping these technologies work together. One of the really strong points of the book is the collection of Web links provided in the footnotes. Following just a few of these links has already proven their worth, and it is likely that the rest will be just as interesting. Online Computing Reviews Service