Natural ecosystems are characterized by a specialization pattern where few species are common, while many others are rare. In ecological networks involving biotic interactions, specialization operates as a continuum at individual, species, and network level. Ecological theory predicts that specialization can be primarily explained by ecological and evolutionary factors. However, we still do not understand how trophic specialization scales from individual- to the network-based level. This question has been addressed by the emerging research program on the macroecology of biotic interactions, which focuses on ecological network and macroecological theory to investigate biotic interaction patterns along environmental and geographical gradients. Based on the ecological and evolutionary traits of interacting species, the study of local networks traditionally focused on interspecific networks or individual species as independent ecological units. Instead, the macroecological perspective requires a shift towards assessing network variation across ecological gradients, while also accounting for different temporal scales (minutes, hours, days, and years), spatial scales (local, regional, and global), and levels of network organization (individuals, species, and assemblages). Despite the feasibility of scaling data, the variation across individual, species and assemblage levels in relation to network organization and geographic and environmental gradients remains unknown. Understanding the mechanisms driving species roles across different network scales is crucial for addressing knowledge gaps, which in turn requires synthesizing and clarifying the available information on these concepts. Thus, in this study we aim to examine the factors shaping trophic specialization at different levels of network organization and to review recent advances, outcomes, and future directions of the field of macroecology of biotic interactions related to specialization. By unraveling the factors and mechanisms that explain the role of each species across different network scales, we shed light on the processes underlying the assembling of natural communities and offer valuable insights into specialization gradients.