How do collaborative networks work in emergency management：based on the analysis of two ways on community detection

With the increasing of departments’ participation, their relationship is becoming more complex than before. As a new interdisciplinary study vision and research paradigm, collaborative network was created in the governance... [ view full abstract ]

With the increasing of departments’ participation, their relationship is becoming more complex than before. As a new interdisciplinary study vision and research paradigm, collaborative network was created in the governance theory. Owe to the development of social network analysis method, visualizing the relationship become possible under the context of collaborative network.

When we talk about this topic, people always realize the ties between different members. That is a reasonable study path, because the network consists of nodes and ties obviously. But that is one-side view, if we are limited in the single subject theory. Actually, when we think about the nature of section, we can find almost every department which is on a scale is separable. All of them can be showed by relation network. In the same way, similar departments can form relative big groups.    

This kind of group can be tested by community detection. This research method can be divided to two branches. The first one is based on non-overlapping algorithm, which can show us different parts of a total collaborative network by clear boundary. The other one is overlapping algorithm, in which we can find shared nodes from multivariate communities.    

In the beginning of this article, we will show the collaborative network structure based on some data from emergency management cases which was collected in China for almost 5 years. According to the structural functionalism theory, function will be considered to explain this structure. Then we will focus on non-overlapping community detection and explore different functions of networks. By doing this, we can simplify networks. In order to explain the ties of communities, in the next step, we will use overlapping detection and research the interaction among shared nodes and relevant communities. Finally, we will contrast two methods’ results and discuss which is more suitable to analyses cooperation processing.