Improving the technique for detecting community structures is important for understanding and controlling complex networks.

Most community detection methods have a high computational complexity and are sensitive to network forms and types.

We propose an algorithm that uses an interaction optimization process to detect community structures in complex networks.

We find that the structure quality and coverage resulting from our algorithm surpass the results of other methods.