Network Science for Social Media

Network Science is another upcoming field of research in social media analytic. In this, for instance, user profiles are treated as nodes and interlinking is framed among them. Based on this interlinking, different analysis are made. These analysis may include information diffusion among networks, coalition among networks, flooding of information or forest fires among nodes and much more.

These problem domains are used when brand affinity or node popularity is required to be checked. There are further two types of nodes namely core node and periphery nodes. Core nodes are those nodes which are linked to many other nodes but periphery nodes are less popular nodes. Thus, core nodes can be the major source for information diffusion.

Moreover, there is lot of concern for time frame and speed issues for interaction among nodes. Replication of data may lead to low accuracy and decrease in speed whereas one to one transmission may lead to increase in time. These factors should be managed. 

One of the approach for the solution of such problems is graph theory. Graph theory is inter-disciplinary field which leads to mathematical results for solutions to complex networks. However, it is believed that optimum solutions can be obtained using graph theory for economical business models. 

More on this can be explored under Network Science concept.

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