2023-2024 Semester 2; 2024-2025 Semester 2; 2025-2026 Semester 1

This three-session course introduces attendees to Gephi, a free and open-source network analysis and visualisation tool. The main focus will be on social network analysis. This is a beginner’s course, no prior knowledge is required.

The first session introduces the basic concepts and techniques of Gephi and dataset construction. It focuses on topics such as:  

• Gephi’s basic concepts (edge characteristics and centrality measures)  

• Preparing data for Gephi in Microsoft Excel  

• Analysing social networks in Gephi (centrality and network level analyses)   

The second session focuses on the plugins of Gephi, and will continue the discussion on dataset construction, the topics will include:  

• Introducing some Gephi’s plugins (GeoLayout and ExportToEarth) 

• Incorporating OpenRefine and Generative AI in preparing a Gephi dataset 

• Designing the attendees own dataset for Gephi in Microsoft Excel  

The third session offers the attendees the opportunity to apply their own dataset in Gephi. 

2023-2024 Semester 2; 2024-2025 Semester 2; 2025-2026 Semester 2

This two-session course introduces attendees to some advanced uses of Gephi in humanities research, such as networks of information transmission, and visualisation and analysis of financial data. This is an intermediate course, basic knowledge of Gephi at the level covered in the ‘Network Analysis from Scratch: Introduction to Gephi’ is assumed, although attendance at the previous course is not required. 

The first session introduces the visualisation of information transmission networks in Gephi. It focuses on topics such as:

• Building information transmission networks using (historical) newspapers

• Applying Gephi’s plugins (GeoLayout) to the network

• Exporting the networks to Google Earth

The second session will focus on the visualisation and analysis of financial data in Gephi, covering topics such as:

• Building dataset for (historical) financial and stock data in OpenRefine and Microsoft Excel

• Quantifying (historical) financial and stock data in Gephi

2023-2024 Semester 2; 2024-2025 Semester 1; 2025-26 Semester 1

Have you seen a presentation on digital research methods and wondered if they are applicable to your work? Are you interested in learning new digital skills but unsure where to start? 

This is the right place for you! 

The digital method of the month meeting is a safe space to freely discuss the practicalities of learning and implementing a new digital skill in your research. 

Each month we select a method, and we have an honest and practical discussion on what it takes to learn and master it. How much time will it take to get the basics? What are the software options available? What are the most common pitfalls? Where can you find more info on the subject?  

The method of this month is Network Analysis. Networks refer to sets of elements and the relationships between them. Network analysis and visualisation use abstraction to represent reality as “dots” and “lines”. By abstracting the messy bundle of qualities typical of empirical reality, this reduction helps reveal patterns and structures in their internal relation. 

2024-25 Semester 1

Data Carpentry develops and teaches workshops on the fundamental data skills needed to conduct research. Its target audience is researchers who have little to no prior computational experience, and its lessons are domain specific, building on learners' existing knowledge to enable them to quickly apply skills learned to their own research. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

This course will cover the following topics:

• Data Organisation with Spreadsheets

• Cleaning Datasets with OpenRefine

• Introduction to Data Analysis with RStudio

This is a beginner level event, and no previous knowledge of the method is required.