Community detection in social networks plays a crucial role in understanding the underlying structure and dynamics of complex systems. In this paper, we present a novel approach for enhancing community detection by refining community boundaries within the framework of Bee Swarm Optimization (BSO). Our method focuses on identifying and contracting the contour of communities, where nodes exhibit greater external degrees than internal degrees, thus enhancing the coherence and granularity of detected communities. Through BSO, we iteratively explore the solution space, employing a contour-based contraction operation to refine community structures. Experimental evaluations on fifteen real-word networks demonstrate the effectiveness of our approach, revealing significant improvements in modularity compared to traditional and state-of-the-art methods.