Group Project

QMUL student assessment pattern 002

In-Class Test 1 (1 hour)

QMUL student assessment pattern 001

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The structure and dynamics of various complex networks (e.g. World Wide Web, online social, intra/interorganisational, im/export trade networks) are examined. A unified theoretical framework to analyse sociologically relevant phenomena exhibiting complex dynamic network structures (e.g. information diffusion, cultural fads, financial crises, and viral marketing) is the aim. Innovation, to uncover the structural foundations of knowledge creation, transfer, sharing, and diffusion in various empirical domains is emphasised from an interdisciplinary perspective by combining current research on complex networks with contributions from relevant organisational and sociological research.

Educational Area Value 2

Educational Area Value 1

Scheduled learning and teaching - 

Independent study - 

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Granovetter, M. (1985), Economic action and social structure: The problem of embeddedness, American Journal of Sociology, 91 (3), 481-510. 

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Harary, F. (1995), Graph Theory, Perseus, Cambridge, MA 

Jackson, M. O. (2008), Social and Economic Networks, Princeton University Press, Princeton NJ.  

Kadushin, C. (2012), Understanding Social Networks: Theories, Concepts, and Findings, Oxford University Press, New York.  

Lin. N. (2001), Social Capital. A Theory of Social Structure and Action, Cambridge University Press, Cambridge UK. 

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Newman, M. E. J. (2002), The spread of epidemic disease on networks, Physical Review E, 66, 016128.  Newman. M. E. J. (2003), The structure and function of complex networks, SIAM Review, 45, 167-256. 

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Newman, M. E. J. (2004), Who is the best connected scientist? A study of scientific coauthorship networks, in Ben-Naim, E., H. Frauenfelder and Z. Toroczkai (eds.), Complex Networks, pp. 337-370, Springer, Berlin. 

Newman, M. E. J. (2004), Coauthorship networks and patterns of scientific collaboration, Proceedings of the National Academy of  Science of the United States of America, 101, 5200-5205.  

Newman, M. E. J. (2004), Detecting community structure 

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BUS7053P - Complex Networks and Innovation

Complex Networks and Innovation

Identify the main application areas of network analysis and carry out a comparative study of complex networks across different empirical domains.

Academic content

Examine and measure social capital and its main network generative mechanisms, i.e., density, social cohesion, bridging ties, and structural holes.

Engage with interdisciplinary literature combining research from the social sciences, applied mathematics and complex systems.

Disciplinary skills

Develop basic computational skills and apply them to simple empirical problems through the use of network software.

Explain and discuss the principles that guide network formation and evolution and the ways in which network structure can be exploited to achieve certain aims.

Examine the network foundations of a number of phenomena, including information diffusion, viral marketing, and the propagation of financial crises.

Develop a network-based perspective on innovation and identify the structural properties and mechanisms that can sustain or hinder the generation and diffusion of innovation.

Apply analytical skills to the discussion and interpretation of network properties and models.

Carry out critical reading and pursue independent research on real-world networks.

Programme and Module Directory

Complex Networks and Innovation

BUS7053P

15 Credits