| Srl | Item |
| 1 |
ID:
183003
|
|
|
|
|
| Summary/Abstract |
This article explores the spatial and temporal diffusion of political violence in North and West Africa by endeavoring to represent a group leader's mental landscape as he contemplates strategic targeting. We assume that this representation is a combination of the physical and social geography of the target environment, and the mental and physical cost of following a seemingly random pattern of attacks. Focusing on the distance and time between attacks and taking into consideration the transaction costs that state boundaries impose, we wish to understand what constrains a group leader to attack at a location other than the one that would yield the greatest overt payoff. We leverage functional data from the Armed Conflict Location and Event Data project (ACLED) dataset that catalogs violent extremist incidents in North and West Africa since 1997 to generate a network whose nodes are administrative regions. These nodes are connected by edges of qualitatively different types: undirected edges representing geographic distance, undirected edges incorporating the costs of crossing borders, and directed edges representing consecutive attacks by the same group. We analyze the resulting network using spectral embedding techniques that are able to account fully for the different types of edges. The result is a representation of North and West Africa that depicts its empirical permeability to violence. A better understanding of how location, time, and borders condition attacks enables planning, prepositioning, and response.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
ID:
190999
|
|
|
|
|
| Summary/Abstract |
While the location of violent events and their propensity to cluster together in space is increasingly well known, a deeper exploration of their spatiality and spatial evolution over time remains an emerging frontier in “Big Data”-driven conflict studies. The new Spatial Conflict Dynamics indicator (SCDi) introduced in this article contributes to fill this gap, by measuring both the intensity and spatial concentration of political violence at the subnational level. Articulating between point pattern and areal spatial analyses, the SCDi allows conflict researchers and analysts to not just map which regions experience the most violence but to track how the geography of conflict evolves over time. The SCDi identifies four spatial typologies of violence and can leverage political event data from most datasets with locational information and can be used for analyses across large multi-state regions, within a single state, or in more localized contexts. In this paper, we illustrate the SCDi with an application to the case of North and West Africa, analyzing over 30,000 discrete events through a twenty-two-year time span and across a twenty-two-state geographical area. We perform a longitudinal analysis of the SCDi typologies to show how the indicator can inform a theory of the spatial lifecycle of violence in the region. The indicator, therefore, has potential as both an analytic tool and a window on conflict episodes, showing how they can change from conflict initiation through resolution.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|