(Social) Network Analysis

Why Engage in (Social) Network Analysis?

Shane Nackerud

  • Explores relationships between individuals, organizations, and groups that interact with each other
  • Allows researchers and students to understand the structure and behavior of a network of social relationships
  • May be visualized using a variety of tools, allowing new questions as well as facilitating interpretation
  • Mapping the Republic of Letters investigates connections between early-modern scholars created by correspondence, scientific academies, and physical travel

Network analysis explores relationships and connections within a dataset. With network analysis the networks are created by relationships among different content elements rather than the specific content types. A network usually consists of nodes, and links between those nodes.

A social network is defined as a social structure of individuals, who are related (directly or indirectly to each other) based on a common relation of interest. Social network analysis is the examination of relationships between individuals, organizations and other groups that interact with each other as represented in a dataset either created or available. Put simply, social network analysis allows scholars to understand the structure and behavior of a network of social relationships.

Social networks are ancient, but past few years have seen a tremendous growth in online social networking platforms, such as Facebook, Google+, LinkedIn, Twitter, and massively multiplayer online gaming (e.g., World of Warcraft). The data generated by these online networks and the public availability of some of this data has quickened the pace of social network analysis and greatly expanded the potential forms such analyses can take.

Network analysis research, including social network analysis, is often visualized using a variety of tools that help the researcher understand how nodes in a network tie together. These visualization tools also assist in creating research questions, and hopefully allow the researcher to draw conclusions.

Conducting network analysis research allows us to better understand the behavior of nodes in a network in relation to each other which is useful in many different fields:

Network analysis can be used to study food chains in different ecosystems.

Computer scientists use network analysis to study internet traffic and connections in order to build new tools and more efficient modes of delivery.

Law enforcement agencies use social network analysis to study terrorist and criminal communication networks, which allows them to identify leaders and associates.

Online social networks use social network analysis to advance proprietary algorithms that recommend new connections (friends) and profit from personalized advertisements.

For any questions or assistance, please contact us (dash@umn.edu).

Exemplary Projects

Analysis to Animal Welfare Research
(West Central Research and Outreach Center, University of Minnesota CFANS)

Mapping the Republic of Letters
(Stanford University)

Northwestern University, knight lab, Untangled: Investigations

Untangled: Investigations
(knight lab, Northwestern University)

Recommended Tools for (Social) Network Analysis

Learn more about the following tools that can facilitate (Social) Network Analysis


Interactive visualization application that runs in Windows, Mac, and Linux. Open source and free. Currently the most popular software package for creating network graphs.


Visualize complex historical data with graphs and maps. Online tool.


Open Source software platform designed originally for scientists, largely used in biological research, but can graph any network of nodes.


Free, open-source template for Microsoft Excel 2007, 2010, 2013 and 2016 that makes it easier to explore network graphs.

Social Network Visualizer

Free, open source software for social network analysis and visualization. Downloads available for Windows, Mac, and Linux.

NCapture in NVivo

A browser extension that captures content from webpages and social media for qualitative analysis.

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