Creative and Critical Use of Complex Networks
Design and understanding of complex networks through mapping & analysis
This is the introduction of a 3-part guide on mapping, understanding, and analyzing complex networks. For the other parts, view “Mapping Networks” and “Analyzing Data-Networks“.
Understanding complex systems
Complexity is characterized as something with many independent parts interacting with each other in multiple ways. Signaling of neurons in our body, messaging of devices in the telecommunication infrastructure, trading activity between agents in markets, social formations among people are some generic examples of complex systems, where small interactions together constitute a larger whole.
If we want to understand a complex system, we first need a map of its relationship diagram that is composed of nodes and links and make a network form, which is by its very nature the fabric of most complex systems.
A network diagram offers a “common language” that is both visual and mathematical. So, from a network map, we can get qualitative information by reading its actors and relations, as well as do quantitative analysis by computing its connection structure. In fact, we can use this common language to study systems that may differ widely in their nature, appearance, or scope. For example, rather three different systems 1) devices sending messages to each other, 2) film actors connected through taking roles in the same movies, 3) organizations connected through partnerships may have exactly the same network structure. While the nature of the nodes and the links differs widely, each network has the same graph representation, consisting of 4 nodes and 4 links. We can use this simple method to begin studying a variety of complex systems.
Why is network logic significant today?
Let us look at why do networks matter today, although they existed in every society in the history. It is known that ~3000 years ago the ancient Phoenician and Greek colonies formed their trade routes and built network of harbours in the Mediterranean Sea. Whereas today, in the same geography, submarine cables carry messages and enable a global communication system. What we have today, is not just networks as analog or bare life happenings, but networks that are digitized, like the way many aspect of life is digitized. Thus, networks matter today, because electronic and software based communication systems made networks measurable. Only in this day and age, networks are able to reach a global scale and infiltrate into every part of our life. With today’s advanced information technologies the metrics of network effect have become trackable and measurable even in one’s daily course of life, at the same structuring the social world as such.
Use of complex networks
In fact, we all experience the network effect, from email to e-commerce, from social networking to banking, from telecommunication to transportation. We all acknowledged the fact that the world is complex more than ever. It feels both flat –one can email anyone any time– and chaotic –our inbox is inundated with information coming from all directions. Sometimes we are opportunistic about the internet, talking about it as a global good, other times we are pessimistic knowing that we are all under surveillance all the time. In such an antagonistic world that is at once flat and chaotic, the question arises again: Where does power reside and circulate?
Additionally, the state’s tactics in partnership with certain corporations to monitor its own citizens through what has been called “the big data”, the NSA leaks and so on and so forth have also attracted our attention towards an inaccessible but quite magical tool of knowing and predicting of what people want. This indeed was possible through understanding the interrelated or linkable structure of the information generated by many, but as said only open to the reach of a handful of institutions. In other words, network logic have been mystified in the eyes of the public. Only experts in certain fields have been aggregating large amount of data and using scientific tools for mapping and analyzing it on relational basis. Neither the relational data nor the mapping and analysis tools are accessible to the average user.
However, it is a myth that common people has no access to data. We are the data for the governments and corporations who continuously sense our activity. In fact today, a wide array of people pursue projects containing complex data. All such people would benefit from structuring and interlinking their information. Connecting our discrete data sets would generate new knowledge, render complex issues visible and generate crucial discussions that impact us and our communities. The Graph Commons platform is a step to allow you to do so.
Graph Commons
Graph Commons is the first collaborative online platform for making and publishing interactive network maps publicly. It is dedicated to investigative journalism, civic data research, archive exploration, creative research, and organizational analysis.
On Graph Commons, you can collectively compile data about the topics you are interested, define and categorize relations, and transform your data into interactive network maps, discover new patterns, and share your insight about complex issues using a simple interface.
The platform serves both producers and consumers of graphs by linking entities together in useful ways and thereby creating a whole that is greater than the sum of its parts. Graph Commons members collectively experiment in the act of network mapping as an ongoing practice: Search across variety of graphs, invite collaborators to their work and ask to contribute to theirs.
We believe everybody will find a unique way to use Graph Commons in their own connected world. We invite you to join us, and join one another in connecting partial information to explore complex relations that impact us and our communities.
We’d love to hear your feedback at contact@graphcommons.com. Follow @graphcommons on Twitter, subscribe to Graph Commons Journal on Medium, join our Slack chat channel for discussions.
This is the introduction of a 3-part guide on mapping, understanding, and analyzing complex networks. For the other parts, view “Mapping Networks” and “Analyzing Data-Networks“.
