Answers to Common Network Science Questions

What is a network?

A network is a set of nodes and the relations that connect them. Anything that can be represented as a “connect the dots” image is a network. Common networks include: social networks denoting who talks to whom; semantic networks denoting which topic is related to which; twitter networks indicating who retweets whom or who uses what hashtag; alliance and hostility networks indicating which country has a treaty with or is in conflict with which; road networks indicating which cities, business, houses, etc. are connected to which; airline networks indicating which flights are between which airport

Nodes are also referred to as dots, points, and vertices. In addition, you might refer to the nodes by what they represent; e.g., people, tweets, hashtags, cities, and so forth. In network visualizations nodes are often represented as points or circles; however, they might also be represented by images such as a person icon, or the name of the node.

Relations are also referred to as links, edges, lines, ties and connections. In addition, you might refer to different types of edges by what they represent; e.g., friendship, retweeting, ownership, and so forth.


What is social network analysis?

Social network analysis, also referred to as network analysis, is an approach for making sense of complex systems in terms of the way the parts of that system are connected. Network analysis is a type of data science useful for dealing with relational data and graphs.


What types of methods are used in network analysis?

Network analysis tools use graphical, statistical, and various computational techniques to extract networks from other forms of data, analyze networks, compare networks, identify key nodes in networks, identify groups in networks, and visualize the networks.


What is the difference between Social Network Analysis, Network Analysis, Link Analysis and Network Science?

Today the difference is largely historical.  For many people, these terms are interchangeable: network analysis, network science, social network analysis, link analysis, dynamic network analysis, geo-spatial network analysis, hi-dimensional network analysis, meta-network analysis, dynamical networks, and relational analysis.

Historically, social network analysis had its origins in graph theory and anthropology, and to a lesser extend zoology.  It was focused on how direct interactions were structured, and how the structure of those relations, i.e. the social network, constrained and enabled activity. Many of these earliest studies were concerned with assessing the power of individuals due to their position in the network.

Link analysis has its origins in computer science and forensics.  It was focused on how the relations among actors, locations, events, etc. could be understood, visualized, and analyzed to solve problems such as those relating to criminal activity.

Network science was the outgrowth of an interest in many fields in big data and a recognition that the pattern of links among nodes, almost independent of the type of nodes, could constrain activity.  Much of the work in networks science used social media and other large scale digital data for analysis.

Dynamic network analysis is an outgrowth of social network analysis and link analysis and focuses on changes in the networks, network visualization, network change detection, and network evolution.

Geo-spatial network analysis is an outgrowth of social network analysis, link analysis and geo-graphic information systems.  It focuses on the how to represent networks on maps, how to assess similarities and differences in networks in different locations, how to track the movement through networks and space, and how to assess whether there are geographic patterns to the way the social network is structured.

What is network visualization and network visual analytics?

Network visualization and network visual analytics refer to the set of techniques for visualizing one or more networks, and features of those networks.

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