Network Analysis
Like social movement research, the area of Network analysis has many implications for understanding the context and meaning of an individual’s acts in light of conflict and political violence.
Network analysis is one of the fastest growing areas of scientific research. With popular press books like Linked and networking websites like Facebook, the study of networks has transcended from the niche research that it once was and into popular consciousness. Despite being more recognizable as a concept, it remains poorly understood as a theoretical device. Complex analytical proofs and computational simulations describe limitless possibilities for the study and analysis of relational structures without stating which forms are most likely to occur and why. Even data-driven network analysis misses the mark by concentrating too heavily on descriptions of network structures without making clear statements about why and how they matter to the collective behavior under inspection. Possibilities are generated, but probabilities cannot be. All too often, the individual human element is either missing or misconstrued in both the approach and application to understanding what leads to political violence.
ARTIS takes a different approach. In order to better understand the “why” behind groups and social movements, studying how different groups are connected helps illuminate the importance and flow of resources, ideas, and motivations. We seamlessly combine formal theoretic methods with relevant field data using designed questions in context to the subjects under study. Familiarity with the processes and paths of these networks can help highlight patterns, peculiarities, strengths, and weaknesses. Additionally, these elements of networks may also reveal the values systems within different groups. Whether studying the evolving relations of terrorist networks or how friendship networks reduce the likelihood that individuals turn toward violence, our aim is to use our insights to provide researchers and policymakers with clear, empirically founded understanding.