What is terrorism? What can we learn and what cannot we learn from terrorism data? What are the perspectives and limitations of the analysis of terrorism data? Over the last decade, scholars have generated unprecedented insight from the statistical analysis of ever-growing databases on terrorism. Yet their findings have not reached the public. This book translates the current state of knowledge on global patterns of terrorism free of unnecessary jargon. Readers will be gradually introduced to statistical reasoning and tools applied to critically analyze terrorism data within a rigorous framework.
Debunking Seven Terrorism Myths Using Statistics communicates evidence-based research work on terrorism to a general audience. It describes key statistics that provide an overview of the extent and magnitude of terrorist events perpetrated by actors independent of state governments across the world. The books brings a coherent and rigorous methodological framework to address issues stemming from the statistical analysis of terrorism data and its interpretations.
- Uses statistical reasoning to identify and address seven major misconceptions about terrorism.
- Discusses the implications of major issues about terrorism data on the interpretation of its statistical analysis.
- Gradually introduces the complexity of statistical methods to familiarize the non-statistician reader with important statistical concepts to analyze data.
- Use illustrated examples to help the reader develop a critical approach applied to the quantitative analysis of terrorism data.
- Includes chapters focusing on major aspects of terrorism: definitional issues, lethality, geography, temporal and spatial patterns, and the predictive ability of models.
Table of Contents
1. Introduction: The Role of Statistics in Debunking Terrorism Myths
2. Myth 1: We Know Terrorism When We See It
INTRODUCTION: THE NECESSITY TO INTERPRET
TERRORISM DATA WITH CAUTION
NO CONSENSUS ON THE DEFINITION
DISCREPANCIES AMONG DATABASES
SIDE EFFECTS OF DISTINGUISHING TARGETS
STATE REPRESSION AND NON-STATE TERRORISM: INSIGHT FROM THE DRC
POLITICAL AND NON-POLITICAL TERRORISM:
LESSONS LEARNED FROM PAKISTAN
CONCLUSION: GUIDING PRINCIPLES OF
THE ANALYSIS OF TERRORISM DATA
3. Myth 2: Terrorism only aims at killing civilians
INTRODUCTION: A NOTE OF CAUTION ON
THE VALIDITY OF THE ANALYSIS OF TERRORISM DATA
HALF OF THE TERRORIST ATTACKS DO NOT KILL
MEASURING AND INTERPRETING TERRORISM CASUALTY IS AFFECTED BY DATA CLASSIFICATION
WITNESSING UNPRECEDENTED LEVELS OF TERRORISM VIOLENCE: A FOCUS ON THE ISLAMIC STATE
CONCLUSION: TERRORISM DOES NOT INELUCTABLY EQUATE WITH THE DEATH OF CIVILIANS
4. Myth 3: The vulnerability of the West to terrorism
INTRODUCTION: ASIA AND AFRICA IN THE LINE OF FIRE
ONE QUARTER OF ALL ATTACKS WORLDWIDE OCCUR IN IRAQ
THE MOST TARGETED CITY BY TERRORISM
CONCLUSION: THE MOST VULNERABLE REGIONS TO TERRORISM ARE IN ASIA AND AFRICA
5. Myth 4: A homogeneous increase of terrorism over time
INTRODUCTION: IDENTIFYING TERRORISM TRENDS BEYOND VISUALIZATION
RISE OF TERRORISM IN ASIA AND AFRICA
NO TEMPORAL PATTERN IN THE WEST?
RISE OF DEADLY CASUALTIES IN ASIA AND AFRICA
NO TEMPORAL PATTERN IN TERRORISM DEATHS IN THE AMERICAS AND OCEANIA?
HIGH LEVELS OF TERRORISM PERSIST IN VERY FEW COUNTRIES
DYNAMICS OF TERROR EVENTS AND DEATH TOLL IN THE WORLD’S MOST TARGETED CITY
CONCLUSION: AN UNEVEN TEMPORAL VARIABILITY OF TERRORISM ACROSS CONTINENTS, COUNTRIES, AND CITIES
6. Myth 5: Terrorism Occurs Randomly
INTRODUCTION: THE DETECTION OF SPATIAL PATTERNS RELIES ON SPATIAL LENSES AND SCALES
IS TERRORISM RANDOM?
WHY SHOULD WE CARE ABOUT SPATIAL AUTOCORRELATION?
CHOOSING RELEVANT LENSES TO EXPLORE SPATIAL DATA
TOBLER’S LAW APPLIED TO TERRORISM
SPATIAL INACCURACY: WHAT DOES THAT MEAN IN PRACTICE?
IN THE BULL’S EYE!
NO DICE ROLLING FOR TARGET SELECTION: THE IRAQI EXAMPLE
CONCLUSION: TERRORISM IS CLUSTERED AT VARIOUS SPATIAL SCALES
7. Myth 6: Hotspots of Terrorism are Static
INTRODUCTION: THE DYNAMIC NATURE OF HOTSPOTS OF TERRORISM
CONTAGIOUS AND NON-CONTAGIOUS FACTORS THAT CAUSE THE SPREAD OF TERRORISM
TYPE OF TERRORISM DIFFUSION IS ASSOCIATED WITH TACTICAL CHOICE
SCALE AND MAGNITUDE OF THE CLUSTERING PROCESS ASSOCIATED WITH ISIS ATTACKS PERPETRATED IN IRAQ ()
LOCALIZING AND QUANTIFYING THE REDUCTION OF ISIS ACTIVITY FROM JANUARY TO DECEMBER
EXPLAINING AND VISUALIZING DIFFUSION OF ISIS ACTIVITY FROM JANUARY TO DECEMBER
CONCLUSION: CHANGE IS THE ONLY CONSTANT IN TERRORISM
8. Myth 7: Terrorism cannot be predicted
PREDICTION OF TERRORISM: A STATISTICAL POINT OF VIEW
STOCHASTIC MODELS FOR THE STATISTICAL PREDICTION OF TERRORISM PATTERNS
PREDICTING TERRORISM: LIMITATIONS, OPPORTUNITIES AND RESEARCH DIRECTION
ARTIFICIAL INTELLIGENCE TO SERVE COUNTERTERRORISM?
MACHINE LEARNING ALGORITHMS TO PREDICT TERRORISM IN SPACE AND TIME: A CASE STUDY
CONCLUSION: PREDICTING TERRORISM IS A PROMISING BUT BUMPY AVENUE OF RESEARCH
9. Terrorism: Knowns, Unknowns, and Uncertainty
Andre Python is ZJU100 young professor of Statistics at Zhejiang University. His current research interests are in extending statistical models to address policy-relevant issues raised by the spread of phenomena threatening global security and health. In 2017, Andre completed a PhD in Statistics at the University of St Andrews, applying a Bayesian spatiotemporal model to capture fine-scale patterns of non-state terrorism across the world. As postdoctoral researcher at the University of Oxford, he has developed geostatistical models and actively contributed to the design and teaching of Bayesian statistics and R software courses for PhD students and University staff.
"The book presents incredibly fascinating research, and can be interesting and useful not only to specialists but to general public for understanding and making informed judgments on terrorism and its debunking with help of statistical data analysis and prediction to prevent future attacks…Each chapter suggests mathematical definitions, glossary, and additional reading sources. Besides those, the book supplies with bibliography of 153 most recent works and multiple links to the internet sites.."