What is Social Network Analysis?

Instructor: Elizabeth Wamicha

Elizabeth teaches undergraduate courses in Business and Information Technology for the last 7 years. She is currently on course to completing a Doctorate in Information Systems

This lesson provides an overview of Social Network Analysis or SNA. SNA provides a platform for obtaining critical insights of various population segments making up social networks.

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.

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