No abstract

One of the most powerful aspects of social network data is the fact that they can reproduce social relationships in a formal and comparable way. Relational matrices abstract from the hustle and bustle of everyday interaction, and systematise information in terms of presence or absence of ties expressing them in a directed or undirected, binary or valued form. While the formal approach represents an advantage of social network analysis, as it allows bracketing off the idiosyncratic and subjective content of social structures, the mathematization of the complex nature of social relationships has also been criticised for the lack of engagement with the subjective meaning and context of relationships. Such stream of critique has called for an increase of use of qualitative methods in social network research. The first goal of the paper is to address these critiques by rebalancing the argument and showing how social network analysis has always engaged with both formal and contextual aspects of social structures. The paper reviews some theoretical perspectives that discuss and systematise a mixed method approach, and explores the methodological advantages of using network visualizations together with qualitative interviews in the collection, analysis and interpretation of personal networks. The advantages of adopting a mixed method approach are illustrated over some examples of friendship networks of 23 single male and female people collected in Milan, Italy, in 2005. A classic name generator is used to reconstruct their egonets of friends, and the visualization is adopted as the input for in-depth interviews with specific attention devoted to the meaning of friendship relationships, the kind of resources they offer, the conflicts and constrains they entail, and how they have developed and evolved over time. By comparing information obtained respectively with name generators and in-depth interviews, the paper shows how the mix of data improves and specify the understanding of personal networks.

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Much of the work in the sociology of science observes scientific communities from a micro perspective, focusing on interactions in laboratories in order to uncover the impact of social and cultural norms in the everyday production of scientific results. Other studies approach the topic from a macro perspective, analysing scientific organizations and the reciprocal influence they have with wider society, or uncovering the invisible colleges that become apparent through the analysis of co-authorship and citations' patterns. Less attention has been paid to the meso level of interaction within and between scientists and the institutions they work in. This paper extends the structural approach of Lazega et al. (2008. Catching up with big fish in the big pond? Multi-level network analysis through linked design. Social Networks 30, 157-176) and analyses the local system of public funding to physics in Italy using bipartite networks. Data cover 10 years of funding of Projects of National Interest (Prin) from the Italian Ministry of University and Research. The micro level (collaborations between scientists), macro level (collaborations between institutions) and meso level (the combination of network measures at a micro and macro level) of interactions are independently analysed, and results are used to model the total amount of money physicists have received over the 10 years against the variables that meaningfully describe the network structure of collaborations. Results show that in order to be successfully funded what counts more than being a big fish (a scientist with a lot of connections) working in a big pond (a large University), is being in a brokerage position interacting over the years with different research groups.

In sociology of science much attention is dedicated to the study of scientific networks, especially to co-authorship and citations in publications. Other trends of research have investigated the advantages, limits, performances and difficulties of interdisciplinary research, which is increasingly advocated by the main lines of public research funding. This paper explores the dynamics of interdisciplinary research in Italy over 10 years of scientific collaboration on research projects. Instead of looking at the output of research, i.e. publications, we analyse the original research proposals that have been funded by the Ministry of University and Research for a specific line of funding, the Research Projects of National Interest. In particular, we want to see how much interdisciplinary research has been conducted during the period under analysis and how changes in the overall amount of public funding might have affected disciplinary and interdisciplinary collaboration. We also want to cluster the similarities and differences of the amount of disciplinary and interdisciplinary collaboration across scientific disciplines, and see if it changes over time. Finally, we want to see if interdisciplinary projects receive an increasing share of funding compared to their disciplinary bounded counterparts. Our results indicate that while interdisciplinary research diminishes along the years, potentially responding to the contraction of public funding, research that cut across disciplinary boundaries overall receives more funding than research confined within disciplinary boundaries. Furthermore, the clustering procedure do not indicate clear and stable distinction between disciplines, but similar patterns of disciplinary and interdisciplinary collaboration are shown by discipline with common epistemological frameworks, which share compatible epistemologies of scientific investigations. We conclude by reflecting upon the implications of our findings for research policies and practices and by discussing future research in this area.