NUSC Summer School in Network Analysis 2020

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Monday, June 8, 2020 to Friday, June 12, 2020
University of Greenwich London, England

Event Details

NUSC Summer School in Network Analysis 2020

With cautious optimism that the worst of Covid-19 will be behind us by June, the Networks and Urban Systems Centre (NUSC) at the University of Greenwich is offering the ninth edition of our Summer School in Network Analysis in London, June 8 -12th, immediately following Sunbelt in Paris.

 

Doing Research with SNA: Tools, Theories and Applications

08 June - 11 June 2020

This four-day introductory course is aimed at researchers, professionals 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. Instructors: Riccardo De Vita, Guido Conaldi.

 

Greenwich Accelerated Development Programme (GADPro)

Networks of International Trade, Investment and Production

08 June - 12 June 2020

This five-day course is aimed at researchers, professionals and post-graduate students interested in network applications of international trade, investment and production. The objective for this course is to enable attendees to develop an understanding of international trade, investment and production network data and gain insights on recent research in the field using network analysis and identify potential research gaps. Guest speakers will showcase leading -edge examples of network applications in the field. Participants will 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. Instructors: Sara Gorgoni, Zheng Zhu, Matthew Smith.

 

For further details: https://www.gre.ac.uk/bus/events/nusc/home