Applied Social Networking - Reducing Complexity?

I was curious about the relevance of social networking technology (SNT) in terms of its practical applicability and usefulness for other fields of science. Researching along science, social networking and complexity helped me to gain some insights on this topic.

As with most new, highly digital-related technology, a decent evaluation is required in order to evaluate the potential of such a new technology to transform from a nice-to-have into a valued and constantly-used everyday application or a science-enhancing tool. By just superficially looking at the two core benefits of todays SNT, namely measurement and visualization, the impact for sciences becomes very obvious.

As an undeniable underlying factor in everyone`s life, social networking technology has been facing a tremendous improvement process based upon the advancement of information technology within the last decades as more and highly sophisticated visualization.

Freeman’s Overview in the Journal of Social Structure provides a good and well-structured overview about the earliest attempts of pre-SNTs towards nowadays sophisticated digital visualization modelling softwares. From first hand-drawn maps based on ad-hoc rules, the article describes the emergence of systematic methods and includes the integration of computer technology. The final paragraphs deal with newest web-based depiction applications that extend the user ability towards network data interaction and monitoring structural properties.

It very much helps to understand how pictorial visuals and analysis in general correlated ever since in science. Consequently, with increasing complexity and analysable dimensions, the scientific benefit increased as well.

All complex systems nowadays and the actions of their components share one common attribut: they are connected / intertwined. This implies that individual components interact in such systems only together with other sets of components. The linkages between these networks can be real or simply a matter of convention, depending on the specific system that is enforced. Such large-scale socio-technical systems make it obvious that science can not examine their properties by sticking to single-disciplinary methods and theories

The real benefit I got to know was the fact how SNT can be applied in this aspect. Whenever combined theoretical constructs from different sciences like sociology, psychology, physics, biology, etc. Become utilized, SNT provides the ability to take all this into account and model, simulate and develop a visual depiction of that specific case. As I mentioned before, the precise multiscale computer simulations enable scientists not only to map such cases but also to analyze interactions between the components of a social network infrastructure.

As I followed up on latest developments in the field of social network simulation, I came across scientific research of the Network Dynamics and Simulation Science Laboratory at the Virgina Tech University.

This is where SNT really comes into practice and constitutes how it helps to reduce complexity and thus making it managable. I highly recommend reading through the articles posted on the website under Selected Publications as they directly show practical application. Main reserach topics focus on the simulation of disease outbreak and their spread. Especially in a closer connected world, the spread of diseases is a high risk. With regards to this aspect, the term of Pandemia gained popularity lately. In such cases, it is an enormous benefit being able to predict the progression of a pandemia or to follow-up backwards, e.g. how the virus went through different stages of transformation by implementing SNT.

The picture gives an idea about a disease spread along four generation of contacts visualized by SNT. It indicates how broad the ranges becomes after only a very few transmission steps.

Source: Scientific American

The information I found firstly helped me to gain an understanding of complexity in a scientifc sense. Even more did I learn about how SNT can be designed and utilized in order to reduce such complexity and by that, gain valuable insights within a vast range of topics, be it medical prevention, backward follow-up or public infrastructure just to name few.

Taken all this into consideration and adding the ability of simulating interaction within SNTs, I am convinced that SNT is indeed able to reduce complexity and thus seems to be a very valuable concept of approaching current and future complex problems.

Depending on your computer literacy, I can higly recommend this website from the International Network For Social Network Analysis that provides a huge portfolio of free downloadable Social Networking Visualization Software. It takes some time to get used to some of the programs but usually they come with good editor notes. Thus, you can really experience the development.

Best regards,

Peter J. Cramer

M10