Contribution of graph theory to the understanding of social dynamics

Abstract

This review article examines how graph theory has contributed significantly to understanding social dynamics by discussing its applicability to social network analysis. A predominantly qualitative study was carried out, with a scoping review design aimed at understanding how this set of tools facilitates studying human interactions and the structure of social groups. The main results highlighted key concepts such as centrality, clusters, connectivity, and network resilience, as well as their applications to analyzing social phenomena such as information diffusion, opinion formation, disease spread, and social cohesion. In addition, the methodological challenges and limitations of graph theory were examined, to propose future directions for interdisciplinary research that delve into the interaction between mathematics and social sciences, especially Social Psychology applied to collective behavior and the social network analysis.

Community resilience: the case of Asunción Ixtaltepec Oaxaca

“…Estos resultados fueron contrastados en la literatura, donde las fuentes especializadas mostraron que en otras comunidades afectadas la prevención formaba de la herencia, pero también aparecía como un bloque importante de cara a la organización de las acciones en la fase recuperación, lo que muestra que la conducta proactiva puede ser un importante factor protector ante las consecuencias negativas en la salud física y mental colectiva. (58,59)…”