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 network 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.