<p>Selection of influential nodes is a crucial task in social networks, as they are widely used for viral marketing, information flow control, public opinion building, etc. While extensive research exists on this problem, most prior studies focus on algorithmic strategies such as approximation, greedy, or heuristic-based approaches, with limited attention to multi-criteria perspectives. This article aims to bridge this gap by conducting a Systematic Literature Review (SLR) of the last decade’s research on influential node selection using Multi-Criteria Decision Making (MCDM) methods. The need for this review arises from the growing complexity of network influence scenarios, where multiple conflicting criteria must be considered for effective decision-making. Through this study, we synthesize findings on the various criteria used, the MCDM methods applied, the techniques to assign weights to the criteria, and the performance evaluation methods adopted. In addition, we examine the datasets utilized and highlight key challenges faced in applying MCDM techniques for influential node selection. This SLR also provides insights into the various datasets used by researchers, and the challenges in the selection of influential nodes using MCDM-based methods are also investigated.</p>