The title of this book might imply, at first sight, a US-centric approach to the topic, but in fact, the contributions are not only from the US, but also from Canada, the UK, Italy, France, Singapore, Hong Kong, India, and Israel. This edited volume consists of 24 chapters, from 57 authors.

The book is organized into two parts: Unit 1, “Methodological Issues in Terrorism Research,” consists of 10 chapters; Unit 2, “Terrorism Informatics to Support Prevention, Detection, and Response,” consists of 14 chapters.

Chapter 1, “Domain Mapping of Contemporary Terrorism Research,” uses self-organizing maps, content map analysis, and co-citation analysis to identify 42 key terrorism researchers. This chapter highlights a shift of focus from viewing terrorism as a low intensity conflict (LIC) to seeing it as a strategic threat to world powers during the period between 1965 and 2003.

Chapter 2, “Research on Terrorism: A Review of the Impact of 9/11 and the Global War on Terrorism,” points out the increasing number of researchers currently working in the field, as well as the greater level of collaboration that now exists, together with the increasing use of both descriptive and inferential statistics.

Chapter 3, “Who are the Key Figures in ‘Terrorism Studies’?,” first develops an analytical framework, and then uses it to identify three pools of researchers: core, central, and peripheral. Interestingly, both Stohl--who has 136 citations in the list of references for chapter 1--and Ronfelt--with 95 citations--are missing from this list of references.

Chapter 4, “Interviewing Terrorists: A Case for Primary Research,” argues that “field research is not only viable but represents a research tool which we need to seriously exploit and subject to comparative analysis.”

Chapter 5, “Resolving a Terrorist Insurgency by Addressing Its Root Causes,” focuses on both the “terrorist life cycle”--formation, leadership, and organization--and the “terrorist attack cycle”--operations, weapons, and targets--in locating terrorist insurgency within a political, socioeconomic, religious, and/or psychological context.

Chapter 6, “A Quantitative Analysis of ‘Root Causes of Conflict,’” uses latent semantic analysis to measure conflict indicators, such as geopolitical instability and socioeconomic or regional inequality, on a corpus of European news articles.

Chapter 7, “Countering Terrorism with Knowledge,” provides an overview of terrorism knowledge bases maintained by the National Memorial Institute for the Prevention of Terrorism (MIPT) and others.

Chapter 8, “Toward a Target-specific Method of Threat Assessment,” presents a threat assessment model for estimating the attractiveness of specific facilities to terrorist organizations.

Chapter 9, “Identifying and Exploiting Group Learning Patterns for Counterterrorism,” proposes a model for the analysis of organizational learning within terrorist groups.

Chapter 10, “Homeland Insecurity: Data Mining, Privacy, Disclosure Limitation, and the Hunt for Terrorists,” discusses the searching of multiple databases and, in the process, highlights the matching problem and selective revelation, without compromising the confidentiality of individuals.

Chapter 11, “Case Study of Jihad on the Web: A Web Mining Approach,” proposes the development of automated/semi-automated procedures and systematic methodologies for, first, capturing Jihad terrorist Web site data and, then, analyzing it.

Chapter 12, “Studying Global Extremist Organizations’ Internet Presence Using the Dark Web Attribute System: A Three Region Comparison Study,” uses automatic Web crawling to collect extremist online presence, and then uses the Dark Web Attribute System to analyze it.

Chapter 13, “Content Analysis of Jihadi Extremist Groups’ Videos,” discusses the use of content analysis and a multimedia coding scheme for examining video type, group modus operandi, production features, and relevance of videos to group goals.

Chapter 14, “Analysis of Affect Intensities in Extremist Group Forums,” uses an affect lexicon, constructed using probabilistic disambiguation, to measure and visualize hatred and violence, which turn out to be strongly correlated.

Chapter 15, “Document Selection for Extracting Entity and Relationship Instances of Terrorist Events,” concentrates on the extraction of entities and relationships from documents, as a precursor to producing a pattern-based ranking scheme.

Chapter 16, “Data Distortion Methods and Metrics in a Terrorist Analysis System,” describes a sparsified singular value decomposition method of data distortion--a critical component in the preservation of privacy in security related data mining.

Chapter 17, “Content-Based Detection of Terrorists Browsing the Web Using an Advanced Terror Detection System,” describes an advanced terrorist detection system that tracks down suspected terrorists by analyzing the content of the information they access on the Web.

Chapter 18, “Text Mining the Biomedical Literature for Identification of Potential Virus/Bacterium as Bio-terrorism Weapons,” uses instance-based learning and text mining to identify candidate viruses and bacteria from the biomedical literature, as potential bioterrorism weapons.

In chapter 19, “Leveraging One-Class SVM and Semantic Analysis to Detect Anomalous Content,” results from a semantic anomaly monitoring system show that natural language processing outperforms the bag of words categorization of documents, in the context of insider threats within the intelligence community.

Chapter 20, “Individual and Collective Analysis of Anomalies in Message Traffic,” focuses on the following four properties of intercepted messages, for further scrutiny: external content (sender, receiver, time and date sent, and length), author, mental state, and emotional state. It argues for a two-pronged approach to detection and analysis of message sets, rather than individual messages.

Chapter 21, “Addressing Insider Threat Through Cost-Sensitive Document Classification,” discovers that logistic regression yields better classification performance than linear discriminant analysis or support vector machines, in terms of cost, lowest false positive rate, and relatively low false negative rate.

Chapter 22, “Using Web Mining and Social Network Analysis to Study the Emergence of Cyber Communities in Blogs,” proposes a framework for the study of hate groups in blogs that comprises blog spider, information extraction, network analysis, and visualization.

Chapter 23, “Automatic Extraction of Deceptive Behavioral Cues from Video,” constructs a set of discrete and interrelational features using two-dimensional (2D) spatial inputs extracted from videos. The chapter analyzes these features using both discriminant analysis and multivariate regression.

Chapter 24, “Situational Awareness Technologies for Disaster Response,” describes situational awareness technologies within the context of the RESCUE Project (http://www.itr-rescue.org/).

A particularly good feature of this book is the back matter included at the end of each chapter: suggested readings, online resources, and discussion questions; I found the Web links particularly useful.

This edited volume should appeal to the growing terrorism informatics research community, graduate students, and readers in the wider community who have an interest in the area.