Social Network Analysis Purpose & Examples | What is Social Network Analysis? | Study.com

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Social Networks

Social networks have been described as social interactions and personal relationships. Social networks can be built on dedicated websites and other applications that provide a platform for users to interact with each other by posting comments, messages, articles, images and other types of information. Facebook, Twitter and LinkedIn and examples of popular social network platforms. Social networks also include offline interactions such as work-groupings, teams or even whole organizations.

Social Network Analysis (SNA)

Social Network Analysis experts such as Orgnet have described SNA as the measurement and mapping of various aspects or relationships between people, organizations, and groups. It also includes mapping these groups of people to computers, sites that they visit and other types of information sources. The SNA graphical representation is made up of nodes and links between nodes. The nodes in the network represent the people and the links between the nodes represent the information flow. The SNA provides a platform for the mathematical analysis of human relationships which in most cases may be a bit difficult to analyze. In the case of SNA, two nodes are said to be connected if they regularly interact or talk in some way. These networks can be built such that they clearly represent the participants in the network, their location, the node (or person) that is at the core of the network and the nodes that are at the periphery. There are three main types of insights that the SNA provides. These are Degree Centrality, Closeness Centrality and Betweenness Centrality.

Degree Centrality

Researchers who are interested in social networks will usually measure the activity of a network for a specific node by using the term degrees. The term degree is defined as the number of connections that a node possesses. For example, the number of direct friends or connections that a person has on Facebook. Given a particular network, if a certain node has the highest number of connections then this node is said to be the hub or connector of the social network. There is a dominant assumption that the more connections a node has the better, however, in the case of social networks, it is not the number of connections a node has that matters but whether these connections lead to even more links with nodes. Degree Centrality is able to provide information about the number of direct hops that a node has to other nodes within the network. Degree centrality is useful in determining connected individuals or very popular individuals. These would also be those individuals that possibly hold the most amount of information in a given network and about the network.

Closeness Centrality

This aspect describes nodes that are connected in such a way that they can access other nodes in the network very easily. This is indicated in the pattern of their indirect ties. It is calculated by adding up the sum of the shortest paths between a given node and all other nodes on the network. A node is said to be central if it is in close proximity to all other nodes. Individuals in a social network that have the highest level of Closeness Centrality would be those who have the highest ability of reaching the entire network quickly. They may act as the salesmen of a given social network or the main broadcasters for the network.

Betweenness Centrality

This aspect describes roles that do not necessarily have the highest number of connections but are placed in close proximity to nodes that do. They therefore act as ‘brokers’ within the social network. This is a powerful role as they connect broadcasters or hubs or even network clusters that would otherwise not be connected. Nodes with Betweenness Centrality have a significant ability to influence the social network. These nodes act as the experts or mavens for a social network cluster and would usually understand the dynamics of social networks very well. They will also usually have the authority to manage collaboration between nodes. This aspect can be used to analyze the dynamics of communication within a network.

Lesson Summary

This lesson examines the important aspects of Social Network Analysis. Social Network Analysis attempts to investigate relationships and interactions of people within social networks. Social Network Analysis provides insight in three main areas – Degree Centrality, Closeness Centrality and Betweenness Centrality. Degree Centrality is used to describe nodes representing individuals who have the highest number of connections, these are individuals that hold the most amount of information about the network. Closeness Centrality is used to describe nodes that are in close proximity to all other nodes. They act as broadcasters of information to most nodes in a social network. Betweenness Centrality is used to describe nodes that are well placed to connect broadcasters or hubs or even separate network clusters who would otherwise not be connected.