Modeling complex social scenarios using Culturally Infused Social Networks

Modeling complex real world scenarios require representing and analyzing information from multiple domains including social, economic and political aspects. However, most of the current frameworks in social networks are not generic enough to incorporate multi-domain information or to be applied in different scenarios. Current frameworks also make simplifications in other modeling aspects such as incorporating dynamism and providing multi-scale analyses. Representing culture is critical to truly capture the nuances of various social processes. It also helps to make the framework generic enough to be applied in multiple application domains.We will leverage a novel framework called the Culturally Infused Social Network (CISN) to represent culture using probabilistic reasoning networks called Bayesian Knowledge Bases (BKBs), in representations known as cultural fragments. Cultural fragments model the intent of actors by relating their actions to underlying beliefs and goals. CISN also supports analysis algorithms to make predictions and provide explanations. We validate CISN by simulating the 2006 Somali conflict involving the Islamic Court Union (ICU). The Somali conflict is a complex scenario requiring deep understanding of myriad factors. We focus on analyzing the group stability of ICU, how changing alliance caused conflicts and led to its ultimate demise. We define a metric to measure instability in a group, identify critical factors that led to instability in ICU and provide analyses.