SNA - Social Network
- Dudi Rozental
- Aug 1, 2007
- 3 min read
Written in collaboration with Tali Helman
Social Network Analysis (SNA) is the mapping and measuring of relationships and information flow between people, groups, organizations, computers, or any other group that generates and consumes information and knowledge.
The nodes in networks are people or groups, while the connections between them represent the relationship or information flow between nodes.
SNA provides visual and mathematical analysis of relationships and connections between people.
In every network, one can identify "players" - individuals who participate in the network and "nodes" through which information flows and analyze their degree of centrality for the network. Social network analysis allows examination of several dimensions: symmetry - the extent to which hierarchical or equal relationships exist between players in the network; reciprocity - the extent to which players respond to each other in the network; multiplexity - the extent to which connections in the network are multi-layered; network strength - the frequency of connections between players; centrality - the extent to which a player is central; mediation - the extent to which a player mediates between other players; types of connections, and more.
To understand networks and their members, we evaluate the position of players in the network and measure the centrality of nodes.
Social network research focuses on revealing patterns and behavior patterns of interaction between people.
SNA is based on representing the intuitive tendency of the lives of the items represented in them.
Network research claims that a person's way of life depends largely on the way of life of the person to whom they are connected socially. Moreover, some argue that the successes or failures of organizations sometimes depend on the behavioral patterns prevalent in their internal structure.
The diagram describes the "Kite Network," developed by David Krackhardt, a leading researcher in social networks. Two nodes in the network are connected if they talk to each other regularly or have some interaction between them. In the diagram, Andre communicates regularly with Carol but not with Ike. Therefore, Andre and Carol are connected, but there is no connection between Andre and Ike.
This network demonstrates the distinction between the three types of measured centrality: Degree Centrality, Betweenness Centrality, and Closeness Centrality.
Degree Centrality: Examines the number of people who approached the player for advice or help (Indegree) and the number of people the player approached for advice or help (Outdegree). It can also be called star centrality. The Indegree and Outdegree are sometimes good indicators of a player's informal status in an organization. For example, people with a high degree of knowledge in an advice relationship network are those with experience who know how to give advice. In contrast, those with high Outdegree tend to approach others.
In the diagram, Diane has the highest number of direct connections in the network, making her the most active node.
Betweenness Centrality: This measure examines how much the player mediates between other players not connected in the network. The mediation ability increases directly to the player's exclusivity over bridges between sub-clusters. The higher this measure, the more it appears that the player has the potential for dialogue and perhaps influence different parts of the network that do not have direct connections and can leverage resources.
A player with high Betweenness is a gatekeeper for information flowing through the network. This player is connected to others, not connected to the network, which is why Betweenness is also called mediating centrality.
In the diagram, Heather has fewer direct connections than Diane, who has the most direct connections. However, Heather has one of the best positions in the network. She is situated between two central regions and embodies the role of a broker in the network. Her role in the network is significant, and without her, the flow of information and knowledge toward Ike and Jane would stop.
Closeness Centrality: Defined by the extent to which one social entity can be exposed to the information, positions, and behaviors of others in the network.
Today, social network analysis is used widely. Applications include mapping and measuring disease spread in hospitals. In global organizations, SNA supports improving innovation in groups of scientists and researchers, helps map managers' social networks through email message flow, and more.
INSNA (International Network for Social Network Analysis) is a global organization involved in social network research. It is a professional association for researchers interested in the subject. INSNA is a non-profit organization established in 1978 and based in and operates in the United States.
Comments