Natural systems are modeled by networks with nodes and links. Often, the nodes are segregated into communities with different connectivity patterns. Node heterogeneity such as political affiliation in social networks or biological function in gene networks is highlighted as a key factor driving the segregation of nodes into communities. Here, by means of numerical simulations, I show that node heterogeneity is not a necessary requirement. To this end I introduce the Ramsey community number $r_{\kappa }$, the minimum graph size that guarentees the emergence of network communities with almost certainty. Using the stochastic block model and Infomap methods for community detection, I show that networks generated by local rules have finite $r_{\kappa }$ values, while their randomized versions do not have emergent communities. I conjecture that network communities are an emergent property of networks evolving with local rules.

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• Community structure
• Emergence of patterns
• Network formation & growth
• Complex networks