Despite being considered as key indicators of research impact, citations are shaped by factors beyond intrinsic research quality-such as including prestige, social networks, and research topics. While the Matthew Effect explains how prestige accumulates, our study contextualizes this by showing that other mechanisms also play a role in citation accumulation. Analyzing a large dataset of U.S. economic (N = 43,467) and their citation linkages (N = 264,436), we find that close ties in the collaboration network are the strongest predictor of citations, closely followed by semantic similarity between citing and cited papers. This suggests that citations are not only driven by prestige but are strongly affected by f social networks and intellectual proximity. Prestige remains an important factor affecting citations for highly cited papers, but for most papers, proximity-both social and semantic-plays a more significant role. These findings redirect focus from extreme cases of highly cited research to the overall citation distribution, which influences most scientists' career paths and knowledge production. Recognizing the diverse factors influencing citations is critical for science policy and for developing a reward system of science that is fairer and reflects a diversity of contributions to science.