Session 1 – Wednesday 6 October
Session 2 – Wednesday 13 October
This two-half day online training event is led by Dr Diarmuid McDonnell [University of the West of Scotland] and is aimed at researchers and analysts from any disciplinary background interested in employing network analysis for social science research purposes.
Vast swathes of our social interactions and personal behaviours are now conducted online and/or captured digitally. Thus, computational methods for collecting, cleaning and analysing data are an increasingly important component of a social scientist’s toolkit. Social Network Analysis (SNA) offers a rich and insightful methodological approach for uncovering and understanding social structures, relations and networks of association.
This training series introduces participants to core concepts, data structures, and methods of analysis associated with SNA. The training consists of a mix of lectures, coding demonstrations, practical exercises, and group discussions. The training is suitable for individuals new to SNA and looking to gain a good grounding in the fundamentals of this methodology.
By the end of the two sessions participants will be able to:
• understand fundamental concepts and terms associated with social network analysis, collect, clean and reshape social network data
• analyse social networks using a variety of summary statistics
• use Python to conduct social network analyses
Participants need access to a computer with a working internet connection. No specialised software is needed.
This course will be run via Zoom.