A Machine Learning Based Model of Boko Haram

In: Terrorism, Security, and Computation Ser.

Abstract

Intro -- Foreword -- Preface -- Contents -- Chapter 1: Introduction -- 1.1 Organization of this Book -- 1.2 How to Read This Book -- 1.3 Summary Statistics About Boko Haram's Violent Activities -- 1.4 Summary of Significant Temporal Probabilistic (TP) Rules -- 1.5 Summary of Policy Recommendations -- 1.6 The Most Feasible Policy Recommended to Combat Boko Haram -- 1.7 Conclusion -- References -- Chapter 2: History of Boko Haram -- 2.1 Emergence and History of Boko Haram -- 2.1.1 Boko Haram's Beginnings -- 2.1.2 The Boko Haram Uprising -- 2.2 Boko Haram -- 2.2.1 A Decade of Terror -- 2.2.2 Timeline of Events -- 2.3 Organizational Overview -- 2.3.1 Structure and Finance -- 2.3.2 Areas of Operation -- 2.3.3 Membership -- 2.3.4 Tactics -- 2.3.5 Training -- 2.4 Relationships with Other Terrorist Groups -- 2.4.1 al-Qaeda -- 2.4.2 ISIS -- References -- Chapter 3: Temporal Probabilistic Rules and Policy Computation Algorithms -- 3.1 Boko Haram Data -- 3.2 Temporal Probabilistic Rules -- 3.3 Policy Computation Algorithm -- 3.4 Sample Predictions -- 3.5 Conclusion -- References -- Chapter 4: Sexual Violence -- 4.1 Sexual Violence in the Absence of Seeking Religious Rule -- 4.2 Sexual Violence in Relation to Imprisoned and Foreign Members -- 4.3 Occurrence of Sexual Violence in Relation to Imprisoned, Foreign Members and Other Variables -- 4.4 Occurrence of Sexual Violence when Members of BH Are Imprisoned, and BH's Communications Did Not Address the Government -- 4.5 Lack of Sexual Violence when Boko Haram's Offices Are Not Shut Down -- 4.6 Lack of Sexual Violence when Boko Haram Is Not Using Child Soldiers -- 4.7 Lack of Sexual Violence when Military Aid Has Been Suspended or Denied and BH Is Not Forcefully Recruiting People.