As more and more people connect via the web, social network analysis software has become instrumental to understanding complex relationships and changing demographics. At their simplest level, these tools can reveal the elements of a network and the many connections. However, there are far deeper complexities within social networking, including factors such as influence, cross-network links, and concepts like "betweeness" that this software can also analyzed and display.
Why Bother Analyzing Social Networks?
As with many computerized tools, analysts prize social network analysis software for its ability to quickly and clearly show how situations change depending on various factors. For example, any social network is made of at least two basic types of elements: nodes, which are the building blocks, and edges which are the connections between the nodes. Examples of nodes, in social networking terms, are things like organizations, individuals or specific areas of knowledge. Edges, on the other hand, are the relationships between those nodes. Examples of edges include a friendship, a family bond, or simply a recommendation on LinkedIn between a freelancer and a company.
By analyzing these relationships, many new aspects of social networking can be discovered. For example, a network may be weighted towards a particular individual, who becomes influential to more and more people as the network grows. A company hoping to quickly spread an idea (or "meme") throughout the network could do it most efficiently by starting with this particular individual (or whatever other form that node takes).
There is an entire science to social network analysis, and this is only one example. The application of these processes has been used for many purposes, including:
- Company Team Building
- Hiring Special Knowledge Workers
- Diversity in the Workplace
- Journalism
- Anti - Terrorist Strategies
- Technology Network Threat Assessment
- Analyzing Personal Influence within Organizations
- Contagious Disease Control
With such a diverse number of applications, it's easy to see why this kind of software is in high demand.
Sources for Social Network Analysis Software
Almost all of the analysis software out there for social networking enable the user to visualize the social network graphically - usually with the nodes represented by various sizes and colors of dots connected by the edges represented by lines (sometimes of varying lengths, colors, etc.). Other variables can also be represented along the X and Y and even Z axes to show other factors, including
- Prestige and influence
- Path length of connections
- Path distribution
- Network density
- Analysis of Clusters
Because of the immense utility of this kind of software, there are many different options available, ranging from free and open source to custom-made and proprietary business software. They are also available for various computer platforms including Windows, Mac, and Linux. Some of the versions available for purchase also advertise training for staff to be able to use the software most effectively, but this is also available to the open-source community through forums and other peer-supported social networks.
SocNetV: an Open Source Example
Licensed under the GNI General Public License, the "Social Networks Visualizer" is a free tool that mathematically graphs networks using hand-entered data, imported files such as Pajek, or by generating them randomly. Developed primarily for Linux, it can work on other platforms, but tends towards a sparse and utilitarian user interface.
Purchasing Analysis with InFlow
For users less familiar with statistical analysis and desiring less of a learning curve, a commercial product such as InFlow can provide many different kinds of graphic representations of networks, organizations, and other forms of data correlating connections and resources. InFlow features very easy changing of metrics, within "2 clicks of the mouse" according to the website, and also provides extensive training to novices.
These are only two examples of software used for analyzing social networks. Others include iGraph, Keyhubs, and NetMiner.
No longer the purview of research labs at universities, the science of social networking has become big business, and using this software can make the difference in anyone's social network strategy.
