Social Networks Analysis is a discipline dealing with the mapping and evaluation of relationships and information flow between people, groups, organizations, computers, or any other group which creates and consumes information and knowledge. The 'nodes' in these networks are the people/groups while the connections between them represent the relationships or information flow between the nodes. SNA provides mathematical and visual analysis of the relationships and connections between people. In every network, we can identify "players" (individuals participating in the network) and "Nodes" through which information flows. We can also analyze how central they are to the network.
An analysis of social networks allows reviewing several aspects: symmetry- the degree in which hierarchical or egalitarian relationships are conducted between different players; mutuality- the degree in which players react to one another; multiplicity- the different layers of the relationships in the network; The strength of the network-the frequency of the relationships between the players; The centrality of different players; mediating- the degree and frequency the player mediates between other players; types of relationships, etc.
In order to understand the networks and their members, we evaluate the players' each node.
The study of social networks focuses on revealing templates and behavioral patterns of interaction between people. SNA is based on representing the intuitive tendency of the lives of the items presented in them. Network research claims that a person's way of life is greatly affected by the life of the person to which he/she is connected to socially. Furthermore, some claim that the successes or failures of organizations are usually related to behavioral patterns conducted in their inner structure.
The diagram describes a 'Kite network' as it was developed by David Krackhardt, a leading researcher in the field of social networks. Two nodes in the network are related to one another only if they speak with each other on a daily basis or interact somehow. In the diagram above, Andre communicates with Karol on a regular basis, but not with Ike. Therefore, Andre and Karol are connected, while Andre and Ike are not.
This network clearly presents the distinction between the three evaluated types of centrality:
Degree Centrality, Betweenness Centrality, and Closeness centrality.
Degree: the number of people who turned to the player for consultancy or help (in degree) as well as the number of people the player turned to for consultancy or help (out degree). This can also be referred to as 'Star Centrality'. The in degree and out degree are usually good indicators for the player's informal status in the organization. For example, players with high in degrees in consulting-relationship networks are experienced players who can therefore share good advice. Those with a high out degree tend to turn to others.
In the diagram, Diana has the highest number of direct relationships in the network. This makes her the most active node.
Betweenness: volume- how much the player mediates between other players that are not connected to each other in the network. The mediating ability is correlated to the degree of exclusivity of this playe's mediation between sub-groups. It seems that the higher the indicator, the higher the player's potential for communication and possible affecting different parts of the network which are not directly related, and therefore the player can exploit these resources. A player with high betweenness is a gatekeeper for information flowing through the network. This player is a player connected to others who are not connected to the network. This is why betweenness is also referred to as "mediating centrality".
In the diagram, opposed to Diana is Heather who has the least direct connections. Yet Heather still has one of the best positions in the network. She is between two central sections and plays the role of 'network broker'. Her role in the network is essential and without her the flow of knowledge and information towards Ike and Jean would cease.
Closeness: the degree one social entity can be exposed to information, opinions and behaviors of others on the network.
Nowadays, the use of social network research is increasingly growing. An application of the subject can be found at hospitals in order to map and evaluate the spread of a disease. In global organizations, SNA supports improving innovation in groups of scientists and researchers, assists in mapping managers' social networks by flowing the information in email messages, etc. A global organization which deals with the study of social networks is the INSNA (International Network for Social Network Analysis). The organization is a professional organization for researchers interested in the subject. The organization is a non-profit association, established in 1978 in the US, where it is active to this day.
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