MATHEMATICAL AND COMPUTATIONAL PERSPECTIVES OF MISINFORMATION DYNAMICS: MODELLING, ANALYSIS AND CONTROL

Source abstract

The spread of misinformation in online social networks and its control has become one of the most significant challenges for modern day researchers. The rapid expansion of social media, online communication platforms, and digitally mediated information has transformed the way information is created, shared, consumed, and perceived. Alongside the enormous benefits of this transformation, there has been a corresponding increase in the speed and scale at which misleading, false, and manipulated information can spread across communities. The consequences may extend beyond individual beliefs and behaviours, influencing public discourse, social interactions, health-related decisions, and the functioning of institutions. Understanding misinformation dynamics therefore requires more than identifying individual false claims. It requires an understanding of the mechanisms through which information propagates, the characteristics of individuals and communities that participate in its transmission, and the factors that can enhance or suppress its spread. In this context, mathematical and computational modelling provides a valuable framework for studying misinformation as a dynamic phenomenon. The present book, Mathematical and Computational Perspectives of Misinformation Dynamics: Modelling, Analysis and Control, brings together contributions that explore different mathematical, computational, and interdisciplinary perspectives on this emerging area of research. The central motivation behind the volume is to view misinformation not merely as a collection of isolated false statements, but as a dynamic process involving interacting individuals, information networks, behavioural responses, technological platforms, and intervention mechanisms. Mathematical models can provide a simplified representation of these complex processes and allow researchers to investigate questions that may be difficult to examine through empirical observation alone. Concepts from dynamical systems, differential equations, network science, epidemiological modelling, game theory, stochastic processes, and computational methods can be adapted to investigate the emergence, persistence, and control of misinformation. Such approaches can also help identify conditions under which misinformation may decline naturally, persist within a population, or require targeted interventions. At the same time, mathematical modelling should not be viewed in isolation. The interpretation of a model depends on the assumptions on which it is constructed and on the quality of the empirical evidence used to motivate and validate those assumptions. Consequently, meaningful progress in misinformation research requires interaction among mathematics, computation, data science, social science, communication studies, and related disciplines. This volume is intended to contribute to that interdisciplinary dialogue. The chapters present different perspectives on misinformation dynamics, modelling approaches, computational techniques, and possible intervention strategies. Some contributions focus on theoretical aspects, while others emphasize applications and computational investigations. Together, they illustrate the potential of mathematical and computational thinking in addressing a problem that is inherently complex and rapidly evolving. Research in mathematical modelling provides an opportunity to connect abstract mathematical concepts with contemporary real-world problems. Through such problems, students and young researchers can encounter mathematics not only as a theoretical discipline but also as a language for describing, analysing, and understanding complex systems. I believe that encouraging young researchers to work at the interface of mathematics, computation, and applications can play an important role in developing the next generation of interdisciplinary researchers. The field of misinformation dynamics is still developing, and many important questions remain open. The increasing influence of artificial intelligence, automated content generation, recommendation algorithms, verification systems, and rapidly changing digital platforms will create new challenges as well as new opportunities for mathematical and computational research. This book is therefore not intended to provide a final account of the subject. Rather, it is an attempt to contribute to an evolving research area and to encourage further investigation. I hope that this volume will be useful to researchers, teachers, postgraduate students, and others interested in mathematical modelling, dynamical systems, computational science, data-driven approaches, and the broader study of misinformation. More importantly, I hope it will encourage readers to explore new connections between mathematics and contemporary societal problems.