Answers to Common Network Science Questions

A network is a set of nodes and the relations that connect them. Anything that can be drawn as a set of dots connected by lines is a network: social networks, semantic networks, Twitter retweet and hashtag networks, alliance and conflict networks among countries, road networks, and airline route networks.

Nodes are also called dots, points or vertices, and are often named for what they represent (people, tweets, cities). They may be drawn as circles, icons or labels. Relations are also called links, edges, lines, ties or connections, and are often named for their type (friendship, retweeting, ownership).

Social network analysis is an approach to understanding complex systems by studying how their parts are connected. It is a data science method for relational data and graphs.

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

Today these terms are largely interchangeable; the differences are mostly historical. Related labels include dynamic network analysis, geo-spatial network analysis, high-dimensional network analysis, meta-network analysis, dynamical networks and relational analysis.

• Social network analysis has roots in graph theory, anthropology and, to a lesser extent, zoology. It focuses on how direct interactions are structured and how that structure shapes activity. Early work often assessed an individual's power from their position in the network.
• Link analysis has roots in computer science and forensics. It focuses on understanding, visualizing and analyzing relations among actors, locations and events, often to solve problems such as criminal activity.
• Network science grew from interest in big data across many fields. It holds that patterns of links can constrain activity largely regardless of the type of node. Much of this work uses social media and other large-scale digital data.
• Dynamic network analysis grew out of social network analysis and link analysis. It focuses on how networks change and evolve, detecting change, and visualizing networks over time.
• Geo-spatial network analysis grew out of social network analysis, link analysis and geographic information systems. It focuses on mapping networks, comparing networks across locations, tracking movement through networks and space, and finding geographic patterns in network structure.

These terms refer to techniques for visualizing one or more networks and their features.

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