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Network Density

Network density is the proportion of direct ties (connections or relationships) to the total number of potential ties among members of a network. The members of a network are usually individuals, organizations, or other things depending on the context being studied. Network density can vary from dense to sparse (also referred to closed or open). Dense networks have a high proportion of direct ties to total ties, which is typically characterized by significant sharing and commonalities among network members. Sparse networks have a low proportion of direct ties to total potential ties, which is usually indicative of members who have a low level of sharing and have little in common. Network density, like other social network characteristics, provides insight into the workings of a network that can influence thoughts and behaviors of its members. This entry describes network density and the history of social network analysis, network density’s primary characteristics, antecedents, outcomes, and aspects of its empirical investigation.

Social Network Analysis

Network density is one measure of a network’s structure and is used along with many other measures (e.g., betweenness, centrality) to study the antecedents and outcomes of networks. Network density is used extensively in social network analysis in different areas of sociology, but also in many other areas such as geography, economics, organizational studies, medical and health, and political science. Social networks are considered to influence the thoughts and behaviors of network members by acts such as the sharing of information and providing of help. These acts can be beneficial to a network member, but they can come at a cost in the form of time and expectations.

Social network analysis originated in the late 1800s and early 1900s with the work of Georg Simmel and Émile Durkheim. One of the views purported by Simmel was the importance of being a member in both small and large networks—that each has something unique to offer. Durkheim also pointed to the importance of social interactions and the structures of networks. In the second half of the 1900s, social network analysis became more comprehensive and formalized based on the ties (relationships) between network members. In this time period, two key network characteristics were identified—strong ties and weak ties. The benefit of strong ties, when close connections exist, was described by David Krackhardt as providing help between network members. The benefit of weak ties, when network members are not well known to each other, was described by Mark Granovetter as providing access to distinct information to network members. Thus, the strength of a tie influences the benefits and costs of being in a network. Network density takes this idea one step further and describes how the proportion of ties within a network influences not only the benefits received but the disadvantages as well.

Network Density Effects

Through communication and action, network members build up understandings of and obligations to one another that guide their cognitions and behaviors in both a restrictive and supportive manner. This is more likely to occur when the relationships among network members are numerous and rich. Dense networks describe this type of network structure. With extensive ties and frequent interactions among network members, members become more fully aware of the thoughts and actions of other members. This provides social cohesion whereby members feel part of a unified group. As part of this group, they are obligated to help one another but also make sure that others are acting in an acceptable manner. Thus, dense network members benefit from the assistance of other members, but they also face limitations in their own behavior.

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