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Scientific collaboration is a complex phenomenon that improves the sharing of competences and the production of new scientific knowledge. Social Network Analysis is often used to describe the scientific collaboration patterns defined by co-authorship relationships. Different phases of the analysis of collaboration are related to: data collection, network boundary setting, relational data matrix definition, data analysis and interpretation of results. The aim of this paper is to point out some issues that arise in these different phases, highlighting: (i) the use of local archives versus international bibliographic databases; (ii) the use of different approaches for setting boundaries in a whole-network; (iii) the definition of a co-authorship data matrix (binary and weighted ties) and (iv) the analysis and the interpretation of network measures for co-authorship data. We discuss the different choices that can be made in these phases within an illustrative example on real data which is referred to scientific collaboration among researchers affiliated to an academic institution. In particular, we compare global and actor-level network measures computed from binary and weighted co-authorship networks in different disciplines

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Over the last decade, the assessment of university teaching quality has assumed a prominent role in the university system with the main purpose of improving the quality of courses offered to students. As a result of this process, a host of studies on the evaluation of university teaching was devoted to the Italian system, covering different topics and considering case studies and methodological issues. Based upon this debate, the contribution aims to present an integrated strategy of analysis which combines both descriptive and model-based methods for the treatment of student evaluation of teaching data. More specifically, the joint use of item response theory and multilevel models allows, on the one hand, to compare courses’ ranking based on different indicators and, on the other hand, to define a model-based approach for building up indicators of overall students’ satisfaction, while adjusting for their characteristics and differences in the compositional variables across courses. The usefulness and the relative merits of the proposed procedure are discussed within a real data set

In the present study, we discuss how social network analysis approach can be fruitful exploited to study social support within family studies. An ego-centred network approach is adopted within a case study about social support networks of low income single mothers living in a city of southern Italy. We address three main issues. First, we aim to describe and explore the structure of social relationships that single mothers activate in order to obtain different kind of supports. Second, we investigate the main factors that affect the amount and variety of resources embedded in the single mothers’ support networks. Third, we analyse the relationship between the received social support embedded in the ego network and the support perceived by mothers. Beyond the description of composition and structure of ego-centred networks through network measures and factorial methods, a series of regression models was estimated to assess factors explaining received and perceived support of single mothers.