Near Real Time Assessment of Emergent Complex Systems of Confederates

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This research seeks to develop new theory, metrics, algorithms and models, and a multi-level modeling workflow for Faction Detection, Dynamics and Influence (FD2I) - i.e., detecting, assessing and forcasting the behavior of factions and their dynamics under alternative courses of action. We view factions as groups with a political focus in their agenda and/or the issues around which they coalesce. Factions are an ever-evolving complex confederated system that can only be understood, and their behavior predicted, within the security context in which they operate on both the cyber and physical plane.

We are developing and testing FD2I theories, empirically driven open-source FD2I models/algorithms, an FD2I multi-level workflow system for operating confederated models, & the tactics, techniques & procedures for reasoning about factions in northern Europe. Using a theoretically transdisciplinary approach that blends social, psychological, organizational, political & computational theory; we draw on multiple types of data including subject matter expertise (SME), political climate information & hostilities data, voting data, economic indicators, news & social media (SM) to instantiate a set of confederated multi-level models & so reason about factions, their narratives & their dynamics. We are developing tools based on the Blau space, Social Influence, & Social Identity theories that given the networks, narratives & demographic information will support the inference of lines of alliance & hostility & the causal factors that will change these. Building on advances in high dimensional network analytics (HDNA), socio-cultural cognitive mapping (SCM), social influence theory, (cyber) collective action theory, formalized Blau space modeling, language technology, machine learning (ML), statistical network theory, & agent-based dynamic-network models (ABMs) we are developing and testing a formal approach for identification & analysis of the factions, their narratives, their dynamics, & their anticipated response to courses of action (COA).