The rapid evolution of cellular networks (4G and 5G), has led to an unprecedented increase in network traffic, driven by both the growing number of mobile users and the escalating data consumption per user. This surge significantly impacts energy consumption and quality of service (QoS). Device to Device (D2D) communication technology has emerged as a promising solution. However, D2D communication encounters substantial chal-lenges, particularly in the domain of energy management. This paper presents a novel social-aware framework designed to address the energy management challenges in D2D communications. It explores how users' social network characteristics can optimize D2D communication for enhanced energy efficiency. The framework in-cludes two innovative methods, SOCICHS and SOCICF, specifically developed for cluster head selection and cluster formation. These methods seamlessly integrate both social and physical information to facilitate energy-efficient D2D communication. Additionally, we propose a comprehensive model for D2D communication man-agement within this framework. To evaluate the effectiveness of the approach, extensive experiments were conducted, involving a maximum population of 1200 users and the consideration of various coefficient values (tau 1 , tau 2). The use of the GOWALLA dataset revealed an average energy efficiency improvement of 25 % and 31 % when compared to base scenarios. Likewise, the analysis of the BRIGHTKITE dataset showed energy efficiency enhancements of 23 % and 32 %. These findings reveal the significant impact of social-aware clustering on energy management within D2D communications. Moreover, the integration of physical features, such as dis-tance, into the framework demonstrated its additional value in achieving efficient energy consumption.