What connects a group of families in Renaissance Florence, a network of Indian Ocean ports and the symptoms associated with mental health conditions? At first glance, these may seem like three very different subjects. However, they can all be studied through a common approach: social network analysis, a method of understanding the relationships and connections between people, places and other elements.
Exploring this fascinating approach to research, the Psychology discipline at the School of Interwoven Arts and Sciences (SIAS), Krea University, organised a two-day Social Network Analysis Bootcamp at the Computational Cognition Laboratory on 31 October and 1 November 2026. Convened by Dr. Rakesh Sengupta, Assistant Professor, Psychology, SIAS, with support from Judith Grace Lazarus, the bootcamp brought together fourteen students from various backgrounds, for an engaging introduction to the fundamentals and applications of network analysis.
“Social network analysis is usually taught as a software course, so students learn to produce a picture before they can say what the picture asserts. We did the opposite. For two days there were no laptops, only chart paper and counting. By Sunday, fourteen students could tell a marriage tie, an inferred trade route and a statistical association apart, even when all three look identical on the page.” – Dr Rakesh Sengupta
Two Days of Exploration
Over six sessions spread across the two days, students worked with different examples to understand how networks function. One of the exercises involved mapping marriage and business relationships among sixteen prominent families in Renaissance Florence. By looking at the connections between these families, students began to understand how relationships could influence the position and importance of individuals within a larger network.
Another exercise took them to the Indian Ocean, where they explored a network of fourteen ports and examined how trade connections linked different locations. They considered what might happen to the larger network if certain ports were removed and how the loss of particular connections could affect the entire system. These activities helped students see how the same principles of network analysis could be applied to very different contexts, from historical relationships to trade and exchange.
The bootcamp also encouraged students to look closer at the social networks around them. Working in groups, participants mapped a small social world using a carefully designed privacy protocol. They identified connections, made observations and recorded predictions about how their networks might be structured. On the second day, these predictions were revisited and compared with computer-generated network diagrams. This gave students an opportunity to see how their observations translated into visual representations and where their initial assumptions stood in relation to the results.
Of learning and Inferences
The discussions also extended into sociology, philosophy and mental health research. Students were introduced to Randall Collins’s work on intellectual lineages and explored how ideas travel through networks of teachers, students and thinkers. The bootcamp also touched upon the concept of horizons of understanding before moving to symptom networks in mental health research. Through a guided demonstration, students learnt how researchers examine relationships between symptoms and why the statistical estimates used to represent these connections need to be interpreted with care.
A central idea that connected the different sessions was that a network diagram does not always tell the complete story. While two diagrams may look almost identical, the lines connecting their different elements could represent entirely different things. They might indicate an actual relationship, an inferred connection or a statistical association. Understanding what these connections represent, and the evidence behind them, is just as important as learning how to draw or interpret a network.
By approaching the subject through practical exercises, the bootcamp gave students an opportunity to engage with a research method without needing prior experience in coding or specialised software. More importantly, it encouraged them to think critically about how information is represented, how relationships are studied and how research methods can be applied across disciplines.
Research Through Hands-on Learning
The Social Network Analysis Bootcamp is part of the Computational Cognition Laboratory’s ongoing efforts to create opportunities for hands-on methods training at Krea. Following the EEG Analysis Bootcamp held in September, this initiative reflects the range of research-oriented learning experiences available to students at SIAS. Through workshops such as these, students get to explore the many ways in which Psychology intersects with history, sociology, philosophy and computational research, while developing the skills to ask questions, examine evidence and understand the world through different perspectives.
