Social Network Analysis

This introductory course is for graduate students who have no prior training in social network analysis (SNA). In the morning, we overview SNA concepts and analyse key articles in the literature. In the afternoon, students learn to handle relational databases and code for SNA research using R.

Link to a key paper in the SNA literature: https://www.jstor.org/stable/2781822?Search=yes&resultItemClick=true&searchText=robust&searchText=action&searchText=padgett&searchUri=%2Faction%2FdoBasicSearch%3FQuery%3Drobust%2Baction%2Bpadgett&refreqid=search%3Ac4254643dc4499f2a9c8608f9e871d96&seq=1#page_scan_tab_contents

• An overview of themes in the literature on SNA
• Searching, producing, and formating relational data
• Basic network statistics using R
• Visualisation of graphs

• Scott, John. 2017. Social Network Analysis. London: Sage Publications Ltd.
• Watts, Duncan J. 2007. Six Degrees: The Science of a Connected Age. New York, NY: Norton.

There may be an online open-book test at the end of the module; for most students, the test is not compulsory.

Click the "Booking" panel on the left-hand sidebar (on a phone, this will be via a link called Booking/Availability near the top of the page).

8 hours - A morning lecture and an afternoon lab session
This is an intensive, one-day module