Predicting hotspots :  using machine learning to understand civil conflict /  Atin Basuchoudhary, James T. Bang, Tinni Sen, John David.

  • Basuchoudhary, Atin,author.
  • Bang, James T.,author.
  • Sen, Tinni,author.
  • David, John,author.
  • Lanham, Maryland :Lexington Books,[2018]
  • xvii,160 pages :illustrations ;24 cm
  • [This book] will be useful to anyone interested in identifying the causes of civil conflict and doing something to end it. Civil conflict is a persistent source of misery to humankind. Its study, however, lacks a comprehensive theory of its causes. This book introduces machine learning to explore whether there even is a unified theory of conflict and, if there is, whether it is a good one. A good theory is one that not only identifies the causes of conflict but also identifies those causes that predict conflict. Machine learning algorithms use sample techniques to choose between competing hypotheses about the sources of conflict according to their predictive accuracy. This theoretically agnostic "picking" has the added benefit of offering some protection against many of the problems noted in the current literature: the tangled causality between conflict and its correlates, the relative rarity of civil conflict at a global level, missing data, and spectacular statistical assumptions. Predicting Hotspots highlights how the sources of conflict affect conflict itself. This additional insight may allow the crafting of policies that match a country's specific circumstance. -- Back cover.
  • (ISBN)1498520677
  • (ISBN)9781498520676
  • (OCoLC)1040230898
  • Social conflict -- Forecasting.
  • Social conflict -- Data processing.
  • Social conflict -- Prevention.
  • Conflict management.
  • Machine learning.