Bike sharing, such as Mobike, are thriving throughout the past three years. Mobike allows users to rent bikes left by previous users. This mobility mode generates self-organized bike distribution over the city. We analyze real data from Mobike bike sharing system in Beijing and Citibike bike sharing system in New York. In this paper, we study the spatial pattern of sharing activity from this new business model. We construct an Origin–Destination spatial network of bike sharing traffic flow based on trip data and study the characteristic of unbalance in the systems. The unbalance of nodes in Mobike bike mobility OD network is revealed to follows a power law distribution with different exponents on weekdays and weekends. We also found that there exists a scaling between maximum unbalance and network degree in both systems. These features of bike sharing can provide a better understanding of sharing mobility behaviors and help to develop more efficient management methods.