Application of a physical model in the study of dynamic co-authorship networks formed from scientific articles

Since the 1970s the application of physics to social situations has been an issue of interest to the scientific community. This branch of physics applies laws and theories to societal behavior at the collective level. These behaviors emerge from the interactions that occur between people. With the present work is carried out an investigation about the scientific community formed from the publications of articles in indexed journals. The data are taken from Web of Science and from these data are constructed co-authorship networks. In this class of networks each node represents the name of an author and each link a collaboration. Our main interest is the analysis of this type of networks over time. For this, as a first step, a script is developed in the R program that allows the extraction of co-authorships from the articles. Subsequently, the analysis of the data will be carried out, using the same programming language, in order to find patterns within this type of networks; based on this analysis will select a physical model that has a behavior similar to the trends found. From the model will be realized a reproduction of the networks employ computational simulations. This project contributes to the work currently carried out on the study of co-authorship networks in search of collaboration patterns of researchers, highlighting our focus on dynamic networks and the selection of a physical model that allows us to predict the evolution that these networks can have; with these results we will have an overview of where the research is headed.