NUSC School in Network Analysis 2020

Summer School 2020

Please note, due to the current circumstances, this event has now been postponed until June 2021.
The exact dates will be advertised soon.

About us

The Networks and Urban Systems Centre (NUSC) is applying the techniques of organisational network analysis to a wide range of business problems, re-conceiving individual firms, organisations and markets as structured relationships.

Our experts have published widely and are working on a range of current research projects including knowledge transfer within the creative industries, high-tech industrial clusters, diffusion through networks, enhanced networking with social media, black and minority ethnic career support networks and inter-organisational networks in micro-finance.

Learning network analysis will give you the tools to solve business problems, influence your organisation and management. It will enable you to be one step ahead of your peers and to find out how professionals relate to one another. Learn about advanced methods, tools, theories and applications in our workshops and hone skills in our accelerated development programme. 

Organisational and economical network analysis is providing powerful insights into the ways people relate to one another within and across organisational boundaries. The techniques allow a rigorous quantification of many aspects of relationships that have previously at best been sensed intuitively.




About the NUSC School


Find out why you should join us at the NUSC school from organiser Professor Bruce Cronin.

Four-day Introductory Course

Doing Research with SNA: Tools, Theories and Applications

Dates TBC

About:

This course is aimed at those researchers and post-graduate students who are new to the field of social network analysis (SNA), and would like to better understand whether and how they can use it to enhance their research programmes. 

The goal of the course is to provide attendees with a general overview of the field of social network analysis, confidence in using its key analytical tools in practice, and insight into how it can be used in scholarly practice in different fields. Focus is on research design and how SNA elements can be successfully integrated into a research project, paper, or dissertation. 

The course offers opportunities to immediately apply the concepts acquired, through daily lab sessions and discussion of published research.

All social science backgrounds are welcome, and participants are assumed not to have any previous knowledge of SNA, or of any analytical or statistical software. Participants will be mainly expected to use RStudio during the course (even if other software will be discussed). No previous experience with the software is expected. RStudio is freely available and can be installed on all operating systems.

Datasets for analysis and lab sessions will be provided, but participants are encouraged to bring their own data

Learning outcomes:

At the end of the course participants will be able to:

  •  independently design a research programme requiring SNA in their own field of research;
  • collect and manage network data;
  • analyse, interpret and visualise fundamental network measures at the individual, group and network level;
  • confidently use RStudio and relevant R packages to perform descriptive network analysis and visualise network data.

The agenda for this course can be found here

Fees

Fees include refreshments, lunch and one social dinner.

Early Bird General - £220
Early Bird Student - £110
*FBUS Staff/Student - £25

*Staff and Students who are apart of the Business Faculty, University of Greenwich are entitled to a discounted rate.

If you are unsure about which ticket you are to purchase, please contact us.

Five-day Greenwich Accelerated Development Programme (GADPro)

Networks of International Trade, Investments and Production

Dates TBC

About:

This course is aimed at Masters/PhD students, researchers and professionals who are interested in network analysis.

The objective for this course is to enable attendees to develop an understanding of international trade, investments and production network data and gain insights on recent research in the field using network analysis & identify potential research gaps. Attendees will also develop software competency in R and Python and be able to apply network analysis methods and techniques, such as descriptive network statistics, network visualisation and community detection.

Relevant network data, methods and literature will be introduced and lab sessions will be provided for hands-on experience.

Themes:

  • Opening Introduction
  • Trade Networks
  • FDI Networks
  • Production Networks
  • Corporate Networks

For each of these themes, the relevant network data, methods and literature will be introduced and lab sessions will be provided for hands-on experience.

This talk includes sessions with external professionals from the relevant fields.

The agenda for this course can be found here

Fees

Fees include refreshments, lunch and one social dinner..

Early Bird General - £460
Early Bird Student - £220
*FBUS Staff/Student - £50

*Staff and Students who are apart of the Business Faculty, University of Greenwich are entitled to a discounted rate.

If you are unsure about which ticket you are to purchase, please contact us.

Accommodation

Please arrange your accommodation directly with suppliers.
The following list of hotels are local to the venue so will be the most convenient for your stay:

Any questions? Get in touch

Find Hamilton House

Located in Park Vista, next to Greenwich park, a short walk from the main Greenwich Campus


Upon arrival to Hamilton House, please ring the buzzer on the left-hand side of the door and report to the reception upon entry.

Unfortunately, the Hamilton House building has no disabled access and there is no on-site parking available.

Learn more about travelling to Hamilton House.

  • DLR Cutty Sark (approx. 11 min walk)
  • Maze Hill (approx. 3 min walk)
  • Greenwich (approx. 15 min walk)
  • Greenwich Pier - Ferry service (11 min walk)
  • TFL buses frequently run close by.
  • Public 'Pay and display' car parks nearby.
  • Campus bus service between campuses.