Social Networks: Theoretically Informed Analysis with UCINET

Social network analysis uses dyadic data (data about the connections between entities) to construct measures of larger structures, such as cohesive groups, bridging individuals, unique positions, or central and peripheral actors. In more general terms, social network analysis is a paradigm that builds theoretical arguments about the impact of triadic or higher order (meso-level) structures on individual nodes, dyads, or macro-level systems. This paradigm is closely related to the relational turn in the social sciences, and provides us with the conceptual tools to avoid falling into traps of structuralism, to formulate arguments that centre on strategic agents exploiting openings in their network structures. 

This course aims to help you build and test such arguments, with the help of network data. Each day will focus on a particular argument, with a reading and hands-on work with data. The readings, software, and data will be provided by the Instructor. We will primarily use UCINET 6, and Gephi 0.9 for analysing and visualising network data. We will use Excel for basic data entry and manipulation tasks.

The first argument we will consider, as an introduction to working with social network data, is about the diversity of the nodes connected. Is diversity related to creative success? 

Day 1
You will learn the basic skills of recording and manipulating dyadic data, and the basics of visualising network data with node attributes. We will discuss fundamental graph theory concepts, such as degree, path, and distance. We also introduce the basics of graph visualisations, such as spring embedders, circular layouts, node and edge size and colour settings, and filterings.

Day 2
This will be about arguments centered on the node level, primarily arguments about the advantages to brokerage (the unique vantage point actors enjoy when they are linked to distinct regions of the network). We will introduce competing measures of nodal prominence (centrality, prestige, and brokerage measures), and visualise the diverse network reach of brokers. We also introduce hypothesis testing at the node level, addressing non-parametric methods appropriate for interdependent observations.

Day 3
The causal significance of cohesion, illustrated through the case of political corruption in business networks. We introduce methods to measure cohesion, and to identify cohesive clusters, and discuss ways to visualise cohesive groups. We also discuss the advantages and disadvantages of methods that identify exclusive or overlapping clusters; the basics of hierarchical cluster analysis, and modularity as a diagnostic.

Day 4
Network multiplexity and power, introducing structural equivalence block-models of multiple networks. We discuss methods of finding and visualising structural equivalence blocks, and introduce goodness of fit measures. We introduce the idea of working with block images, and relational multiplication tables, and talk about the significance and challenges of working with multiplex data.

Day 5
Dynamics of the economic world system, through the networks of international and intersectoral trade. We discuss valued networks, cutoffs, and filterings. Finally, we introduce regular equivalence block-models, and methods to analyse and visualise networks through time. 

Basic knowledge of statistics and probability (probability density functions, tests of statistical significance, ordinary least squares estimator).

Basic knowledge of data entry and manipulation (for example using Excel sheets).

Each course includes pre-course assignments, including readings and pre-recorded videos, as well as daily live lectures totalling at least two hours. The instructor will conduct live Q&A sessions and offer designated office hours for one-to-one consultations.

Please check your course format before registering.

Online courses

Live classes will be held daily for two hours on a video meeting platform, allowing you to interact with both the instructor and other participants in real-time. To avoid online fatigue, the course employs a pedagogy that includes small-group work, short and focused tasks, as well as troubleshooting exercises that utilise a variety of online applications to facilitate collaboration and engagement with the course content.

In-person courses

In-person courses will consist of daily three-hour classroom sessions, featuring a range of interactive in-class activities including short lectures, peer feedback, group exercises, and presentations.

Disclaimer

This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.). Registered participants will be informed at the time of change.

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.