What is a Social Network Analysis?

Viabosque Team
Jan 2, 2024
7 min read

The following article is a primer for individuals and organizations that are new to Social Network Analysis. This tool provides a powerful window into the strength and effectiveness of any network.

What is a Network?

A network is a set of relationships. These ties can be among individual people or organizations.

Why Networks?

Given the complexity of social problems and the unrelenting pressure to reduce the cost of creating and implementing solutions in the face of limited resources, networks offer a way to weave together capacities and build power that can achieve greater impact. Networks demonstrate several desirable characteristics for accomplishing complex tasks. They are flexible, efficient, and innovative organizing hybrids that enable participants to accomplish something collectively that could not be accomplished individually. Networks, coalitions, alliances, and other forms of interorganizational collaboration are seen as more effective strategies for building power to affect broader systems and policy change.

Networks can be vehicles for dissemination of messages, approaches, programs, innovation, and ideas to network members and to the public at large. Networks facilitate and support coordinated action among organizational members.

What is Social Network Analysis?

Network connectivity reflects how well relationships are forming across a network. As the effectiveness of any network depends on the strength of the connections between participants, network connectivity is a critical means of assessing progress — especially in the early days of a network’s formation.

Social network analysis (SNA), also known as network mapping, is the most effective method currently available for visualizing and evaluating a network’s connectivity. SNA offers an empirical way to represent the patterns of connection and disconnection among participants at a given moment in time. Network analysis allows for the examination and comparison of relationships between two organizations (dyads), among clusters or cliques of organizations, and among all of the organizations comprised by the network. This provides important clues about where clusters are forming, how information is flowing, and where to weave relationships.

SNA can be used to capture the degree to which participants have formed a relationship with one another, are communicating (sharing information, ideas, or data), are coordinating (connecting their efforts closely but maintaining separate resources and responsibilities), and collaborating (working in partnership, sharing resources, and making shared decisions). Information can be gathered at regular intervals (i.e., every 6 months) to assess network change over time.

SNA results can support a network’s development in several ways, including:

Assessing the network’s growth over time,
Identifying key influencers and those who are least engaged, and
Highlighting opportunities for intervention and weaving.

Key Terms in Social Network Analysis

Sociogram: a graphic representation of the pattern of relationships that connect individual actors (people or organizations) to each other.

Node: An actor in a network, each represented by a single dot.

Tie: The direct connection between two adjacent nodes, each represented by a line. Density: The overall level of “connectedness” in a network. Density measures the proportion of all the ties in a network that have actually formed relative to all that could possibly form.

Measuring the Network’s Connectivity

SNA metrics allow stakeholders to identify the most and least connected people (measured by degree or indegree), the top bridgers (measured by betweenness centrality), and overall network connectivity (measured by density). Each of the most useful SNA metrics are described below.

Density (overall network connectivity)

The overall level of “connectedness” in a network. Density measures the proportion of all the ties in a network that have actually formed relative to all that could possibly form. Density is usually represented as a number between 0 (0% of possible connections made) and 1 (100% of possible connections made). If the network density is .60, that means that 60% of all the possible connections across the network are actual connections. Another way to think of this is the probability that any two organizations picked at random are connected with one another. This is a very helpful statistic that tells us how well-connected, or how dense, the network is.

Degree, Indegree, Outdegree

Degree is the total number of connections an organization has in the network. Those with a high degree might have more influence or access to information than others in the network. Indegree measures the total number of incoming connections, whereas outdegree measures the total number of outgoing connections.

Indegree is particularly useful when not everyone has completed a survey - measuring only incoming connections helps account for the fact that those who have completed the survey may have many outgoing connections while those who have not yet completed the survey will have none.

Average Path Length

Average Path Length is the average degree of separation between any two organizations in the network. Less connected networks have higher average path lengths, and more connected networks have lower average path lengths. As a network evolves, we hope average path length decreases, as organizations become more connected with each other and have an easier time becoming connected with other organizations in the network. As you add new organizations into the network (or, at least, it into the survey), average path length will go back up.

Diameter

Diameter is the highest degree of separation between any two organizations in the network. If the diameter of the network is five, that means it will take no more than five connections to get from any one organization to any other organization in the network. As the network evolves we hope that this number goes down.

Reciprocity

Reciprocity is the likelihood that an expressed connection from one organization to another is reciprocated back. When there is low reciprocity, this tells us that people responding to the survey have very different understandings of their connections with one another, and there might be a problem or lack of clarity in how the questions were asked in the survey.

Betweenness Centrality

Betweenness Centrality is the degree to which a node (an organization) acts as an exclusive “broker” or “bridge” between two other nodes that would otherwise not be connected. Organizations with high betweenness are bridgers in the network, as they provide essential connectors between organizations. Organizations with high betweenness can also be seen as bottlenecks or gatekeepers between two organizations. Bridgers in networks play a critical yet often hidden role.

Eigenvector Centrality

Eigenvector Centrality is a measure that considers not only how many other organizations a given organization is connected to, but also the connections among those organizations. Organizations with high eigenvector centrality are connected to other well-connected organizations.

Closeness Centrality

Closeness Centrality is a measure of how connected an organization is with every other

organization in the network, on average. Those with the top closeness centrality ranking might have an easier time reaching anyone in the network than others, and their opinions may spread faster than others as well.

Ways to Use SNA

Assessing the network’s growth over time

SNA helps to assess the progress of a network during its formative stages. In particular, it can help leaders evaluate the effectiveness of network convenings in enabling participants to establish and deepen their relationships with one another. Seeing this type of progress, particularly before more tangible outcomes have been reached, can help to show progress and inspire further engagement among funders and participants alike.

Identifying key influencers and those who are least engaged

Social network analyses can also identify the key influencers in a network—the people or organizations others commonly turn to for information, guidance, or support. The organizations listed most often are usually indicated with the largest nodes—these are the key influencers in the network. Meanwhile, the organizations on the periphery of the network are the least engaged, and may need some additional attention or support to find ways to plug in.

Highlighting opportunities for intervention and weaving

Network maps can reveal vulnerabilities and areas that need attention. SNA can reveal how people are clustered together, and where there are opportunities to strategically weave those clusters together. Visualizing the connections (or lack thereof) across this network presents a clear need for weaving—strategically connecting people or organizations with each other—in order to bridge clusters and engage disconnected actors. Deliberate weaving would go a long way towards creating a more connected network, allowing information and resources to flow more effectively.

Questions to Consider When Reviewing Network Maps:

What is the overall level of connectedness among organizations in the network
(density)?
Which organizations are most central or most involved in the network (centrality)?
Are all or most network members connected, either directly or indirectly (that is,
through another organization), or is the network broken up into fragments of
unconnected organizations?
Which agencies are most central in the network?
Which core network members have links to important resources through their
involvement with organizations outside the network?
Are critical network ties based solely on personal relationships, or have they become
formalized so that they are sustainable over time?
Are some network relationships strong while others are weak? Should those
relationships that are weak be maintained as is, or should they be strengthened?.
Which subgroups of network organizations have strong working relationships? How can
these groups be mobilized to meet the broader objectives of the network?
Based on comparative network data over time, has reasonable progress been made in
developing stronger network ties?
What is the level of trust among agencies working together, and has it increased or
decreased over time? If it has declined, how can it be strengthened?
What have been the benefits and drawbacks of collaboration, have these changed over
time, and how can benefits be enhanced and drawbacks minimized?

Weaving a Network

Building and maintaining a network is hard work. Gray (1989) describes the early stage of network development as the ‘‘problem setting phase’’. In this phase, like-minded individuals and groups are convened that ideally represent a wide variety of the community, are perceived as being legitimate stakeholders, and begin to identify that their actions and outcomes are dependent upon the actions of each other. A first step is simply to better understand the existing relationships, centers of power, intersecting issues, and levers for change among all of these parties (Krebs & Holley 2006).

As part of forming a network, stakeholders must agree that their shared goals are important enough to outweigh the costs of such a collaborative effort. Developing a shared identity, shared goals, shared decision-making, and strengthening trust are all important aspects of early stages of network development. Important core tasks that take place in the formation stage therefore include the establishment of an organizational structure and processes that guide network communication, decision-making, and conflict resolution.

Many also stress the importance of a legitimate and skilled convener or lead organization with existing relationships within a community and strong “process capacity”. Lead organizations require the capacity to connect across organizational, sectoral, cultural and geographical boundaries, guide vision and strategy, foster a collective sense of identity, and create a separate holding environment for knowledge sharing, innovation, and development of collective action.