Jan Lorenz – författare

This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network analysis. Empirical cases range from migration policy framing in North America and street protests in Iran to violence against civilians in Congo and food riots world-wide. Supplementary materials in the book include a comprehensive list of the datasets on conflict and dissent, as well as resources to online repositories where the annotated code and data of individual chapters can be found and where (agent-based) models can be re-produced and altered. These materials are a valuable resource for those wishing to retrace and learn from the analyses described in this volume and adapt and apply them to their own research interests. By bringing together novel research through an international team of scholars from a range of disciplines, Computational Conflict Research pioneers and maps this emerging field. The book will appeal to students, scholars, and anyone interested in the prospects of using computational social sciences to advance our understanding of conflict dynamics.

This open access book brings together a set of original studies that use cutting-edge computational methods to investigate conflict at various geographic scales and degrees of intensity and violence. Methodologically, this book covers a variety of computational approaches from text mining and machine learning to agent-based modelling and social network analysis. Empirical cases range from migration policy framing in North America and street protests in Iran to violence against civilians in Congo and food riots world-wide. Supplementary materials in the book include a comprehensive list of the datasets on conflict and dissent, as well as resources to online repositories where the annotated code and data of individual chapters can be found and where (agent-based) models can be re-produced and altered. These materials are a valuable resource for those wishing to retrace and learn from the analyses described in this volume and adapt and apply them to their own research interests. By bringing together novel research through an international team of scholars from a range of disciplines, Computational Conflict Research pioneers and maps this emerging field. The book will appeal to students, scholars, and anyone interested in the prospects of using computational social sciences to advance our understanding of conflict dynamics.

This is an open access book. What holds societies together—and what drives them apart? As worry over political polarization and social cohesion intensifies across the globe, this volume explores timely and vital questions of social cohesion and polarization through the lens of Computational Social Science. It brings together leading and junior scholars who harness the power of computational methods to analyze, model, and understand discourse, social relationships, and beliefs. Drawing on tools such as agent-based modeling, social network analysis, and natural language processing, the book offers a range of innovative approaches to study how belief systems form, attitudes polarize, and communities fragment.Aimed at researchers, students, and practitioners across disciplines, this volume is both an introduction to the field and a showcase of its most promising applications. It is an introduction into CSS of social cohesion and polarization, and an invitation to rethink how we study—and perhaps even how we can repair—the social fabric.

Many people in the Western world are concerned that the social fabric of societies is fraying. This book constitutes the first-of-its-kind systematic account of social cohesion, from theory through methodology to empirical evidence. Readers are introduced to the academically developed Social Cohesion Radar of Bertelsmann Stiftung, a globally active non-governmental organization. The Social Cohesion Radar defines and measures cohesion as characterized by three core aspects: resilient social relations, positive emotional connectedness between people and the community, and a pronounced focus on the common good. Using high-quality academic and institutional data sources, the Social Cohesion Radar provides insights into the level and development of social cohesion over a period of almost 25 years internationally, among 34 European Union and OECD members, and regionally, among the 16 federal states of Germany. It further provides insights into what influences cohesion, and what cohesion is good for. One of the key findings is that social cohesion promotes a happier life for everyone.