DIGITAL COMMUNITIES AND COLLECTIVE BEHAVIOUR - Data, Personality, and Polarisation in the Age of Artificial Intelligence

This monograph offers a clear and comprehensive introduction to the study of digital communities in the age of AI. It brings together methods from computational social science, statistics, and machine learning, showing how digital traces can be collected, interpreted, and contextualised without losing sight of ethical constraints or data limitations. The authors guide the reader through the practical challenges of working with online data – biases, platform constraints, and the “post-API era” – while providing a coherent framework for analysing collective behaviour. Techniques ranging from network analysis to distributional modelling, topic extraction, and large language models are presented with clarity, highlighting both their potential and their limitations. A distinctive contribution of the book is the integration of personality modelling with community structure and polarisation dynamics. By linking individual traits to collective patterns, the monograph illustrates how different analytical levels can be connected to understand why communities form, diverge, or radicalise. Accessible yet rigorous, this volume is suited for graduate students, researchers, and practitioners seeking both methodological grounding and practical guidance for studying digital behaviour. It serves as a bridge between established statistical approaches and emerging AI-based methods, encouraging critical, responsible, and reproducible research.