7A. Network Analysis

(JDrucker 9/2013)

The concept of a network has become ubiquitous in current culture. Almost any connection to anything else can be called a network, but properly speaking, a network has to be a system of elements or entities that are connected by explicit relations. Unlike other data structures we have looked at–data bases, mark-up systems, classification systems, and so on—networks are defined by the specific relations among elements in the system rather than by the content types or components. The term network is frequently used to describe the infrastructure that connects computers to each other and to peripherals, devices, or systems in a linked environment. But the networks we are concerned with in digital humanities are created by relationships among different elements in a model of content.

Good examples of networks are social networks, traffic networks, communication networks, and networks of markets and/or influence. Many of the same diagrams are used to show or map these networks, and yet, the content of the relations and of the entities might be very different in each case. Standardization of graphic methods can create a problem when the same techniques are used across disciplines and/or knowledge domains, so a critical approach to network diagrams is useful.

Exercise: You can sketch a network on paper quite easily. Put yourself at the center and then arrange everyone you know in your immediate circles (family, friends, clubs, groups) around you. Think about degrees of proximity and also connections among the individuals in different parts of your network. How many of them are linked to each other as well as to you. If you can code the lines that connect your various persons to indicate something about the relationship, how does that change the drawing?

What attributes of a relationship are readily indicated? Which are not?

Social networks are familiar and the use of social media has intensified our awareness of the ways social structures emerge from interconnections among individuals. Actor-network theory, or ANT, is a contemporary formulation by Bruno Latour that extends developments in sociology from early in the 20th century work of Georg Simmel and others. A network may or may not have emergent properties, may or may not be dynamic, and may have varying levels of complexity. Simple networks, like the connection of your computer to various peripheral devices through a wireless router in your home environment, may exhibit very little change over time, at least little observable change. But a network of traffic flow is more like a living organism than it is like a set of static connections. Though nodes may stay in place, as in airline hubs and transfer points, the properties of the network have capacity to vary considerably. Networks exhibit varying degrees of closed-ness and open-ness as well, and researchers interested in complex or emergent systems are attentive to the ways boundary conditions are maintained under different circumstances, helping to define the limits of a system. Social networks are almost never closed, and like kinship relations or communications, they can quickly escalate to a very high scale. Epidemiologists trying to track the spread of a disease are aware of how rapidly the connections among individuals grows exponentially in a very short period of time. Network analysis is an essential feature of textual analysis, social analysis, and plays a large role in policy and resources allocation as well as in other kinds of research work.

The basic elements of any network are nodes and edges. The degree of agency or activity assigned to any node and the different attributes that can be assigned to any relation or edge will be structured into the data model. The simplest data models for networks consist of “triples” – three part structures that allow entities to be linked by relations. This is very different in character from the “tuple” or two-part structure that links records and entities, for instance, in the use of metadata to describe an object.

Exercise: Kindred Britain (http://kindred.stanford.edu/)

This is a site that looks at the connections about 30,000 British individuals. The project is meant to show the many ways in which connections form through social networks, family ties, business and political circumstances. Play with it for awhile and then discuss:

  • selection of individuals
  • character and quality of relations
  • explicit assumptions and implicit ones
  • the diagrams and their rhetorical power

Exercise: Republic of Letters (http://republicofletters.stanford.edu/)

Another project produced at Stanford that is focused on understanding the ways in which letters created a virtual community in the 18th century. Look through the various topics within this project and compare one with another. How is the information in the correspondence being used? How are the maps created? How are relationships defined?

Look at this particular visualization: https://stanford.app.box.com/voltaire2

Be sure to look at http://www.e-enlightenment.com/ and see how the data in this repository was used by the Stanford Project.

Exercise: Google “mapping social networks”

Pick any three images and compare them, think about what they do and do not show and how they make use of screen space, maps, and diagrammatic conventions. Then look at the BioPortal at Arizona University and see how the researchers are using network analysis in their work.

Advanced network theory pays attention to emergent properties of systems. The capacity of networks to “self-organize” using very simple procedures that produce increasingly complex results makes them useful models for looking at many kinds of behaviors in human and non-human systems. Networks do not have to be dynamic, systems almost always are. The study of systems theory and of networks is relatively recent, and only emerged as a distinct field of research in the last few decades. We might argue, however, that novelists and playwrights have been observing social networks for much much longer, as have observers of animal behavior, weather and climate, and the movements of heavenly bodies held in relation to each other by magnetism, gravity, and other forces.

Takeaway:

Networks consist of nodes (entities) and edges (relations). The data model for a network is a simple three-part formula of entity-relation-entity. This can be structured in a spreadsheet and exported to create a network visualization. Networks emphasize relations and connections of exchange and influence. Refining the relations among nodes beyond the concept of a single relation is important, so is the change of relations over time. Social networks change constantly, as do communication networks, and the relations among the technology that supports a network and the psychological, social, or affective bonds can alter independently.

Required readings for 7B

  • Dunn, Stuart. “Space as Artefact: A Perspective on ‘Neogeography’ from the Digital Humanities’, in Digital Research in the Study of Classical Antiquity, Ashgate, 2010, 53-69.
  • Goodchild, M. F. “What does Google Earth Mean for the Social Sciences?” in Geographic Visualization: Concepts, Tools and Applications, eds M. Dodge, M. McDerby and M. Turner. John Wiley & Sons, Ltd, Chichester, UK, 2008,

Study Questions for 7B

  1. Stuart Dunn poses a challenge digital geography by asking how it can be used “to understand better the construction of the spatial artefact, rather than simply to represent it.” What does he mean and how does he demonstrate a way to meet this challenge?
  2. What benefits and concerns does Michael Goodchild describe in his discussion of Google Earth as a tool for scholarship. Does he share Dunn’s assumptions about “space as artefact” or not?

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