
Install packages I Graph and Essany in R to enable social network analysis, and demonstrate installing packages and documenting the code for future use in the interface.
Create a Sankei network in R with the Network D3 package, loading a JSON dataset from GitHub to visualize energy flows and regional or national material accounts.
Create a force network to visualize complex relationships in social network analysis using embedded vertex and edge data. Analyze central nodes, adjust parameters, and zoom for clearer visualization across networks.
When it comes to data-oriented programming language, R is considered one of the top 3 in the list. Through R we can perform a staggering number of statistical data modelling functions. In this exciting course we will learn how R can be used to perform social network analysis which is one of the widely used data analysis methods these days to measure connectedness among individuals, groups and organisations. Social network analysis is used to establish and measure connectivity within transport, advertising, national security, medicine, geography, politics, social psychology, and many other fields. If you're involved in analytics in any capacity, this course will be a huge help, teaching you how R can be used to format data for analysis, create graphs, analyse network graphs, and visualise networks. Although the course is designed in an extremely simple but informative manner, but it is still expected that you should be some basic experience of R environment to do this course. The course also comes with some sample data-sets, coding lists and R files with codes which will help you to become an expert of social network analysis. So, let’s learn how to examine the relationships and trends among networks in new and exciting ways, and discover information about how individuals in an organization interact.