Academic team formation as evolving hypergraphs

This paper quantitatively explores the social and socio-semantic patterns of constitution of academic collaboration teams. To this end, we broadly underline two critical features of social networks of knowledge-based collaboration: first, they essentially consist of group-level interactions which call for team-centered approaches. Formally, this induces the use of hypergraphs and n-adic interactions, rather than traditional dyadic frameworks of interaction such as graphs, binding only pairs of agents. Second, we advocate the joint consideration of structural and semantic features, as collaborations are allegedly constrained by both of them. Considering these provisions, we propose a framework which principally enables us to empirically test a series of hypotheses related to academic team formation patterns. In particular, we exhibit and characterize the influence of an implicit group structure driving recurrent team formation processes. On the whole, innovative production does not appear to be correlated with more original teams, while a polarization appears between groups composed of experts only or non-experts only, altogether corresponding to collectives with a high rate of repeated interactions

GED: the method for group evolution discovery in social networks

The continuous interest in the social network area contributes to the fast development of this field. The new possibilities of obtaining and storing data facilitate deeper analysis of the entire network, extracted social groups and single individuals as well. One of the most interesting research topic is the dynamics of social groups, it means analysis of group evolution over time. Having appropriate knowledge and methods for dynamic analysis, one may attempt to predict the future of the group, and then manage it properly in order to achieve or change this predicted future according to specific needs. Such ability would be a powerful tool in the hands of human resource managers, personnel recruitment, marketing, etc. The social group evolution consists of individual events and seven types of such changes have been identified in the paper: continuing, shrinking, growing, splitting, merging, dissolving and forming. To enable the analysis of group evolution a change indicator - inclusion measure was proposed. It has been used in a new method for exploring the evolution of social groups, called Group Evolution Discovery (GED). The experimental results of its use together with the comparison to two well-known algorithms in terms of accuracy, execution time, flexibility and ease of implementation are also described in the paper.Comment: 14 pages, Social Network Analysis and Minin

Global Professional Service Firms and the Challenge of Institutional Complexity : 'Field Relocation' as a Response Strategy

In this paper we use the case of the internationalization of English law firms into Italy, and the refocusing of their operations on the city of Milan, to make a number of contributions to existing literatures on responses to institutional complexity. First, we contribute to the literature on how organizations address complexity at the field level, by revealing the role of 'field relocation' as a particular response strategy. We also identify a number of organizational tactics - re-scoping, re-scaling, and re-staffing - through which 'field relocation' is accomplished. Second, we also show the importance of further developing our understanding of the geography of institutional fields by highlighting how the 'receptivity' of different field locations may affect responses to complexity. This identifies the importance of geographically locating fields and sub-fields in studies of organizational responses to institutional complexity

Harnessing collective intelligence for the future of learning – a co-constructed research and development agenda

Learning, defined as the process of constructing meaning and developing competencies to act on it, is instrumental in helping individuals, communities, and organizations tackle challenges. When these challenges increase in complexity and require domain knowledge from diverse areas of expertise, it becomes difficult for single individuals to address them. In this context, collective intelligence, a capacity of groups of people to act together and solve problems using their collective knowledge, becomes of great importance. Technologies are instrumental both to support and understand learning and collective intelligence, hence the need for innovations in the area of technologies that can support user needs to learn and tackle collective challenges. Use-inspired research is a fitting paradigm that spans applied solutions and scientific explanations of the processes of learning and collective intelligence, and that can improve the technologies that may support them. Although some conceptual and theoretical work explaining and linking learning with collective intelligence is emerging, technological infrastructures as well as methodologies that employ and evidence that support them are nascent. We convened a group of experts to create a middleground and engage with the priorities for use-inspired research. Here we detail directions and methods they put forward as most promising for advancing a scientific agenda around learning and collective intelligence

Network analysis and morphogenesis : a neo-structural exploration and illustration

This chapter looks at the extent to which network analysis and a neo-structural approach to social phenomena can contribute to the morphogenetic approach in exploring the notion of Morphogenetic Society. An initial summary presents network analysis, in combination with other methodologies, as a technique exploring morphostatic and morphogenetic processes at the meso-level of social reality. An empirical illustration suggests that fundamental social processes (solidarity, control, socialization, regulation, etc.) driving the co-evolution of structure, culture, and agency can be further specified and understood within such a dialogue. In order to illustrate this programmatic perspective an example is provided: a network study of a 450-year-old French institution for the social control of markets. The focus is on the surprising resilience of this institution as seen through the cyclical dynamics of a key network (the advice network) operative among its lay judges and their judicial decisions based on normative, cultural choices. This case in point raises the question of when a change of network should be considered enough of a change to constitute a case of morphogenesis. It thus illustrates the need for further specification in theorizing morphogenesis, morphostasis, and homeostasis