Taha Yasseri – författare

As people spend increasing proportions of their daily lives using social media, such as Twitter and Facebook, they are being invited to support myriad political causes by sharing, liking, endorsing, or downloading. Chain reactions caused by these tiny acts of participation form a growing part of collective action today, from neighborhood campaigns to global political movements. Political Turbulence reveals that, in fact, most attempts at collective action online do not succeed, but some give rise to huge mobilizations--even revolutions. Drawing on large-scale data generated from the Internet and real-world events, this book shows how mobilizations that succeed are unpredictable, unstable, and often unsustainable. To better understand this unruly new force in the political world, the authors use experiments that test how social media influence citizens deciding whether or not to participate. They show how different personality types react to social influences and identify which types of people are willing to participate at an early stage in a mobilization when there are few supporters or signals of viability.The authors argue that pluralism is the model of democracy that is emerging in the social media age--not the ordered, organized vision of early pluralists, but a chaotic, turbulent form of politics. This book demonstrates how data science and experimentation with social data can provide a methodological toolkit for understanding, shaping, and perhaps even predicting the outcomes of this democratic turbulence.

As people spend increasing proportions of their daily lives using social media, such as Twitter and Facebook, they are being invited to support myriad political causes by sharing, liking, endorsing, or downloading. Chain reactions caused by these tiny acts of participation form a growing part of collective action today, from neighborhood campaigns to global political movements. Political Turbulence reveals that, in fact, most attempts at collective action online do not succeed, but some give rise to huge mobilizations--even revolutions. Drawing on large-scale data generated from the Internet and real-world events, this book shows how mobilizations that succeed are unpredictable, unstable, and often unsustainable. To better understand this unruly new force in the political world, the authors use experiments that test how social media influence citizens deciding whether or not to participate. They show how different personality types react to social influences and identify which types of people are willing to participate at an early stage in a mobilization when there are few supporters or signals of viability.The authors argue that pluralism is the model of democracy that is emerging in the social media age--not the ordered, organized vision of early pluralists, but a chaotic, turbulent form of politics. This book demonstrates how data science and experimentation with social data can provide a methodological toolkit for understanding, shaping, and perhaps even predicting the outcomes of this democratic turbulence.

Using big data and computational methods comes with unique challenges, and this book shows you how to overcome these in a core element of research: design.

It equips you with the information you need to ask good research questions and shape your research interests into an ethical, well-developed research proposal. At an approachable pace, it:

Demonstrates how design touches every aspect of research, from finding literature to determining data analysis techniques.Offers step-by-step advice on how to produce a high quality research proposal, whether as an end-goal or part of a wider study.Helps you map the research field, covering qualitative, quantitative and mixed methodologies and concepts.

Grounded in examples of computational social science research, this book helps you develop your research design skills and confidently plan your research project.

Relevant case studies and journal articles will allow you to see the concepts you're learning put into practice, and will help you to explore related literature in your discipline. For students across courses relating to social data science and computational social science, this book is a step-by-step guide to help anyone producing a research proposal and project. 

Using big data and computational methods comes with unique challenges, and this book shows you how to overcome these in a core element of research: design.

It equips you with the information you need to ask good research questions and shape your research interests into an ethical, well-developed research proposal. At an approachable pace, it:

Demonstrates how design touches every aspect of research, from finding literature to determining data analysis techniques.Offers step-by-step advice on how to produce a high quality research proposal, whether as an end-goal or part of a wider study.Helps you map the research field, covering qualitative, quantitative and mixed methodologies and concepts.

Grounded in examples of computational social science research, this book helps you develop your research design skills and confidently plan your research project.

Relevant case studies and journal articles will allow you to see the concepts you're learning put into practice, and will help you to explore related literature in your discipline. For students across courses relating to social data science and computational social science, this book is a step-by-step guide to help anyone producing a research proposal and project. 

This accessible Handbook provides a comprehensive exploration and overview of computational social science (CSS), bringing together global experts to examine its boundary-spanning nature. With an interdisciplinary focus, chapters shed light on the transformative power of computational approaches in social science and take a forward-looking approach to anticipate the next wave of innovations in CSS including those driven by generative AI and large language models.Covering diverse topics such as social networks, political behavior, human mobility, and collective intelligence, the Handbook highlights the vast potential of CSS to analyze and understand complex social phenomena. It explores a wide range of methodological approaches, from agent-based modeling and big data analytics to experimental designs and machine learning applications.Designed for students, researchers, and professionals, the Handbook is an invaluable resource for those working and studying in the field of CSS. Its practical insights into the methodologies that have shaped CSS will greatly benefit social science instructors, educators, and industry professionals in social data science and analytics.

The two-volume set LNCS 10539 and 10540 constitutes the proceedings of the 9th International Conference on Social Informatics, SocInfo 2017, held in Oxford, UK, in September 2017.The 37 full papers and 43 poster papers presented in this volume were carefully reviewed and selected from 142 submissions.