Network Of Cooperation And Co-competing Networks

In classical mechanics and classical electromagnetics, the investigation object, motorial matter, considered as been divided into infinitude parts, which tend to be infinitesimal and are consecutive distributed. Motorial matter is regarded as a collection of such parts. These basic parts supposed to be put on regular grid points in the regular space. Therefore, coordinate system, created by mathematician many years ago, can be used to describe the position and position change of all basic parts perfectly. Although every basic part's position in the space is different, generally changing with time, their mutual actions obey simple and universal recognized basic principles. So we can use calculous theory, founded hundreds of years ago, to show universal dynamic laws dominated these external systems.However, are external systems regular or irregular, even distributed or uneven distributed? Are they composed of uniform basic cells or abundant disparate basic cells? Does the position distribution of basic cells affect system's dynamic behavior? This may be the first chief question to be answer when physics extend to complex systems. Complex network emerges as the times require and becomes a powerful tool to investigate complex systems. Netwok description based on simply described models. It's predigestion and abstract of complex world. Such kind of description regarded basic cells as"nodes"in the network and their mutual actions as"edges"between nodes. Then put forward a series of network properties, such as degree distribution, act degree distribution, clustering coefficient, assortativity and so on.There is a very notable character in complex networks, especially social networks. That is this kind of networks have obvious community and clique structure. We mostly investigated clique structures of social and quasi-social networks in chapter three of this paper. A new statistical network property is proposed here. We called it k-clique act degree distribution. Then proposed a simplified network evolvement model and presented detailed analysis of this model. Finally, we did a lot of empirical statistical work. Two-clique act degree distribution and three-clique act degree distribution of many real networks were presented in chapter two. Amazingly, nearly all the distributions we got followed shifted power law (i.e. SPL) distribution, which accorded with the model conclusion. We confered this conclusion maybe universal in a certain extent.As we know, mutual actions between basic cells in real systems are very complicated and various. If we just consider their collaboration and neglect all the other mutual actions, for example the competion relations, the networks are called collaboration networks in this way. And statistical network properties which mainly show collaboration relations between nodes in the network are called collaboration properties, such as act size, act degree and so forth. We have studied four real systems and their special collaboration properties in chapter four.In fact, there is not only collaboration but also competion between basic cells in real systems. It should be more universal that collaboration and competion coexists. Such networks are called collaboration-competion networks in this paper. Since collaboration-competion networks exists universally, how should we describe this kind of collaboration and competion actions? Therefor, we proposed a new property called node weight, which reflects the competion result. Then we calculated total node weight distributions of more than ten real world networks. Surprisingly, all the gained distributions followed SPL distribution. This may be a universal law too. Chapter three and five mainly investigated collaboration-competion networks and the statistical law of node weight in ollaboration-competion networks.