# Co-Authorship Networks Analysis to Discover Collaboration Patterns among Italian Researchers
## 2 Related Works  
Co-authorship networks have been of great interest for several decades [11; 12] and have been one of the main topics in network science research. For instance, in the pioneering work [15], [PERSON] constructed some networks in which nodes are scientists (extracted from bibliographic databases in biology, physics, and mathematics) and two nodes are connected by an edge if they have co-authored almost a paper. Such network were used to study collaboration patterns over time, and how they vary between subjects. [PERSON] highlighted that _\"the co-authorship network is as much a network depicting academic society as it is a network depicting the structure of our knowledge. Additionally, perhaps because of this, it has received far less attention than have citation networks\"_. In [22] the authors presented a study showing how some topological features impact on some bibliographic indices using networks that encompass only a subset of Italian scientists. In addition to the works already mentioned in the introduction that mainly focused on network topological properties, such as the \"scale-free\" and \"small-world\" properties, other authors used the co-authorship networks to evaluate the performance of a set of researchers. [PERSON] et al. [23] exploited the co-authorship networks among the most productive European researchers, over a 12-year time window, looking at the impact of collaboration upon the citations aiming at discovering the best European researchers. [PERSON] et al. [1] examined the impact of early co-authorship on the careers of junior researchers in four specifics scientific. In [24], the authors explored the correlation between centrality metrics in co-authorship networks and Hirsch index [8] (H-index). In [25], the level of collaboration is evaluated through the definition of a specific centrality index called \(\phi\). Other authors examined the evolution over time of the co-authorship networks. For example, [PERSON] et al. [26] studied the dynamics of productivity in different fields of scientific research while [PERSON] [27] proposed a hyper-graph model for simulating the evolution of large co-authorship networks. Of course, whatever is the goal of the study the starting point is always the choice of scientists to study and the construction of the network itself. It is straightforward that the number of scientists included, but also the set of features, the time interval and several other elements could influence the final results, therefore the method and sources selected are fundamental by themselves to guarantee meaningful results. The main contribute of this paper is the description of the strategies used to construct a dataset from which derive the co-authorship networks enriched by several well-established performance parameters. We also explain issues met during the setup, such as the presence of ambiguous or duplicated information, how to manage missing information, how to combine results and so on. The source of bibliometrics information is the Elsevier's Scopus Database [28], while the scientists used as seeds was the Italian researchers belonging to official academic organizations. Although there are many other bibliographic databases available, such as Web Of Science (WoS) [29] and Google Scholar [30], we decide to use the Scopus Database since it is widely recognized in Italy, contains almost all publication types and is used as a reference for many Italian academic ranking by law. However, in literature can be found several examples where co-authorship networks are based on different data sources, such as [31] that extracts data from WoS. Among the recent co-authorship networking available in the literature based on Scopus, [PERSON] et al. [32] proposed a temporal analysis of the co-authorship network of Italian Institute of Technologies, and [PERSON] et al. [33] evaluated the performance of some universities; both selected the authors (nodes of the network) according the authors' affiliation.