From individual to social metrics
Social aggregation, also referred to as flocking behavior, may be defined “[…] as a type of self-organized collective behavior [and is] described as the spatial formation of groups without global control and explicit inter-individual recruitment signals.”.
This behavior can be observed in many animals, birds, fish, ungulates, and of course primates including homo sapiens sapiens. Although spatial components of group interaction have been simulated in a number of mathematical models, only very recently have there been studies on living animals such as fish or birds. Analysis of dynamic flocking behavior is based on mapping collective individualized complexity indices to social metrics. This is a significant step beyond a characterization of behavioral micro-patterns of an individual.
We may consider an illustrative example that we will target in future studies if this proposed feasibility study will be successful as we expect. It is the case of behavioral and psychological symptoms and signs (BPSS) as they are often found in dementia and are mental health disorders. They constitute a major public health problem.
MMS/CassiopéeSocial combination is capable to provide high-precession GPS-based readings of each subject position in space and time. CassiopéeSocial constructs a social network graph based on space-time proximity given space and time duration thresholds. Lastly, it maps individualized behavioral micro-patterns to the constructed community graphs build upon various similarities of, e.g., secondary topological indices, clustering (posture) or similarity (physiology) measures. CassiopéeSocial thus provides a map from individual behavioral patterns to a subgraph clusters