Graffiti as a Predictive Indicator of Social ConflicT
Collecting accurate and timely social data is one of the most consistent challenges in Afghanistan. Nearly all reporting is founded on perception based research, which is highly prone to error and impossible to qualify. Rely on this information for strategic planning and policy construction has dire consequences.
Through ethnographic and design research, I developed alternative tactics to measure issues of conflict, stability, and economic development. One such method was the documentation and assessment of graffiti over time to read into underlying social trends without direct personal engagement. This indirect measure requires additional methods to determine validity, and thus makes stronger use of standard perception based research practices.
The map below identifies areas of social instability according to street art imagery and language. Having documented every graffiti work in Kabul in a short period of time, new graffiti was identified and correlations could be identified to map changing social opinion.
Mapping the Fluidity of Militant Alliances within Afghanistan
Any war scholar will agree on the criticality of involving the right stakeholders to build peace. Yet, in an entrenched conflict space like Afghanistan, after decades of war has affected a multitude of groups and actors, who do you talk to?
Contracted by the US Institute of Peace, I trained a group of Afghan researchers at the Afghan NGO, Centre for Peace and Conflict Studies (CAPS) to conduct direct qualitative interviews with local level Taliban commanders and members of militant groups within multiple provinces. By means of careful questioning and documentation, it was possible over time to model the formation of militant alliances between members of groups and between groups.
From this assessment it was possible to identify key members of the militant groups engaged, the relationship between these groups and the greater notion of the taliban, and to identify key individuals who can liaison between groups to facilitate peace negotiations.
Above: Macro-Visualizations of Anonymized Data by Christopher Warnow (Click for Large View)
Below: Deep Dive Data Analysis for Key Actor Identification and Visualization by Mitch Sipus