  Communities are ubiquitous in nature and society. Individuals that share
common properties often self-organize to form communities. Avoiding the
shortages of computation complexity, pre-given information and unstable results
in different run, in this paper, we propose a simple and effcient method to
deepen our understanding of the emergence and diversity of communities in
complex systems. By introducing the rational random selection, our method
reveals the hidden deterministic and normal diverse community states of
community structure. To demonstrate this method, we test it with real-world
systems. The results show that our method could not only detect community
structure with high sensitivity and reliability, but also provide instructional
information about the hidden deterministic community world and our normal
diverse community world by giving out the core-community, the real-community,
the tide and the diversity. This is of paramount importance in understanding,
predicting, and controlling a variety of collective behaviors in complex
systems.
