Networks in social policy problems / edited by Balázs Vedres and Marco Scotti.

Includes bibliographical references and index.

Print version record.

Network science is the key to managing social communities, designing the structure of efficient organizations and planning for sustainable development. This book applies network science to contemporary social policy problems. In the first part, tools of diffusion and team design are deployed to challenges in adoption of ideas and the management of creativity. Ideas, unlike information, are generated and adopted in networks of personal ties. Chapters in the second part tackle problems of power and malfeasance in political and business organizations, where mechanisms in accessing and controlling informal networks often outweigh formal processes. The third part uses ideas from biology and physics to understand global economic and financial crises, ecological depletion and challenges to energy security. Ideal for researchers and policy makers involved in social network analysis, business strategy and economic policy, it deals with issues ranging from what makes public advisories effective to how networks influence excessive executive compensation.

Cover; NETWORKS IN SOCIAL POLICY PROBLEMS; Title; Copyright; Contents; Contributors; Acknowledgements; 1 Introduction; 1.1 Introduction: applied network science; 1.2 The structure of this volume; Part I Information, collaboration, innovation: the creative power of networks; 2 Dissemination of health information within social networks; 2.1 Introduction; 2.2 Theoretical overview; 2.2.1 Diffusion of health information and interpersonal communication; 2.2.2 The two-step model; 2.2.3 Multi-step model; 2.2.4 Structural characteristics of graphs; 2.2.5 Random graphs; 2.2.6 Modeling dynamic processes

2.3 Data and method2.3.1 Data; 2.4 Computational simulation; 2.4.1 Data preparation; 2.4.2 Learning transmissions; 2.4.3 Modeling diffusion; 2.5 Distribution of individual (vertex) characteristics; 2.6 Conclusion; 3 Scientific teams and networks change the face of knowledge creation; 3.1 Data; 3.2 Findings; 3.2.1 Teams and citations; 3.2.2 Citation impact for solo and team scientists; 3.3 Notes on the link between teams and networks; 3.4 Author networks and team assembly; 3.4.1 Team size in the sciences; 3.4.2 The network; 3.4.3 A plausible model

3.4.4 Assembly rules and journal impact factors3.5 Discussion; 4 Structural folds: the innovative potential of overlapping groups; 4.1 Network structures for access and action; 4.2 Structural folds; 4.3 Instability and coherence; 4.4 Data and methods; 4.4.1 Data; 4.5 Group performance; 4.6 Structural folds and group stability; 4.7 Conclusion; 5 Team formation and performance on nanoHub: a network selection challenge in scientific communities; 5.1 Introduction; 5.2 Voluntary collaborative project teams; 5.3 Mechanisms associated with successful teams

5.4 Translating findings into policy -- an information problem5.4.1 Emergent local dynamics -- the information disadvantage of policy-making; 5.4.2 Emergent collective dynamics -- the information advantage of policy-making; 5.5 Using network analysis to assist policy; 5.5.1 Network analysis and community norms; 5.5.2 Network signatures of emergent norms of team assembly; 5.6 Method; 5.6.1 Inferring community logics; 5.6.2 Dependent/performance variables; 5.6.3 Hypothesis testing; 5.7 Results; 5.7.1 Identifying community logics; 5.7.2 Performance regression; 5.8 Discussion

5.8.1 Review of findings5.8.2 Policy implications; 5.8.3 Limitations and further research; Part II Influence, capture, corruption: networks perspectives on policy institutions; 6 Modes of coordination of collective action: what actors in policy-making?; 6.1 Modes of coordination within organizational fields; 6.2 Coordinating collective action: social movements, coalitions, organizations, subcultures/communities; 6.3 An illustration: Milanese environmentalism in the 1980s; 6.4 Modes of coordination, network organizations, and policy processes

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