Identificando a emergência do componente gigante em redes de citação

The emergence of the giant component in networks has been a topic of study, spanning classical random graph models to more recent developments in social network analysis, complex networks, and network science. However, in the case of citation networks among scientific articles, it remains unclear whether the evolution of the largest components exhibits a phase transition, like other types of networks. If it does, it is uncertain whether indicators derived from these models can help identify the emergence of the giant component. This paper analyzes the evolution of the largest component in the citation networks of five journals published by the American Physical Society: PRA, PRB, PRC, PRD, and PRE. The first four journals have data spanning over 40 years, while PRE has data for 20 years. By comparing indicators from random network models, the study finds that the Erdös-Renyi model is more effective than others in identifying the emergence of the giant component. Additionally, it demonstrates that the evolution of component size can be modelled using logistic regression, which provides another potential indicator for identifying the emergence of the giant component.