Social network analysis (SNA) refers to the systematic study of social structures and the relationships between individuals, groups, or organizations in a specific social system or community. It is a multidisciplinary approach drawing from sociology, anthropology, psychology, and other social sciences to analyze and understand the patterns of social interactions and the flow of information within a given network.
SNA involves the examination of connections, ties, or links among actors within a network, unveiling the underlying network structure and identifying key actors or nodes that play a significant role in information transmission or social influence. These actors can be individuals, groups, or organizations, and the connections between them can be based on a variety of social phenomena such as friendships, communication patterns, collaborations, or information exchange.
The analysis of social networks often employs both visual and mathematical representations to map and analyze relationships and patterns. Visual representations typically take the form of network diagrams or sociograms, allowing for a visual depiction of the network structure and easily identifying central actors or clusters of actors. Mathematical models, on the other hand, help quantify and analyze various aspects of the network, such as the degree of connectivity, centrality, or the strength of ties.
Social network analysis is widely used in various fields, including sociology, organizational studies, economics, public health, and information science. It provides valuable insights into social dynamics, diffusion of information or behaviors, collaboration patterns, and can assist in understanding how social relationships and structures influence individual and collective behaviors and outcomes.