This book explores community dynamics within social media. Using Wikipedia as an example, the volume explores communities that rely upon commons-based peer production. Fundamental theoretical principles spanning such domains as organizational configurations, leadership roles, and social evolutionary theory are developed. In the context of Wikipedia, these theories explain how a functional elite of highly productive editors has emerged and why they are responsible for a majority of the content. It explains how the elite shapes the project and how this group tends to become stable and increasingly influential over time. Wikipedia has developed a new and resilient social hierarchy, an adhocracy, which combines features of traditional and new, online, social organizations. The book presents a set of practical approaches for using these theories in real-world practice. This work fundamentally changes the way we think about social media leadership and evolution, emphasizing thecrucial contributions of leadership, of elite social roles, and of group global structure to the overall success and stability of large social media projects. Written in an accessible and direct style, the book will be of interest to academics as well as professionals with an interest in social media and commons-based peer production processes.

Proposes a new way of thinking about the emergence of online groups Presents a new method for measuring elite stability and group structuration through quantitative research on large, intact data sets Connects traditional sociological and communication literature with big data analysis Introduces real-time analytical strategies that may improve the way we manage online knowledge production systems Includes supplementary material: sn.pub/extras

Autorentext
Sorin Adam Matei, Professor, Brian Lamb School of Communication, Purdue University, Director of the Data Storytelling Network, Purdue University. Dr. Matei specializes in big data research that investigates the evolution of social media collaborative groups. He is also interested in how social ties and social capital emerging in social media groups generate stable social structures and functional roles. His work was funded by the National Science Foundation and was published in article and book format by the Journal of Communication, Communication Research, American Behavioral Scientist, Springer Nature, and other outlets.

Brian C. Britt, Assistant Pro fessor, Department of Journalism and Mass Communication, South Dakota State University. Dr. Britt is a computational social scientist who focuses on the intersection between organizational communication and new media, with a particular emphasis on the strategies employed by individuals positioning themselves in online organizations. His work has been funded by the National Science Foundation and the National Institutes of Health and has resulted in several book chapters in edited volumes.

Inhalt
Introduction.- Part I: Structural Differentiation and Social Media: Theoretical Framework.- Macro-Structural Perspectives on Social Differentiation and Organizational Evolution in Online Groups.- Specifying a Wikipedia-centric Explanatory Model for Online Group Evolution and Structural Differentiation.- Social Structuration Online: Entropy and Social Systems.- Analytic Investigation of a Structural Differentiation Model for Social Media Production Groups.- Part II: Configurational Change Phases and Motors in Online Collaboration.- The Foundations of a Theoretical Model for Organizational Configurations and Change in Online Collaborative Processes.- Organizational Configurations and Configurational Change.- A Synthesized Theoretical Framework for Motors Driving Organizational Configurational Change.- Wikipedia Evolution: Trends and Phases.- Breakpoints and Concurrent Factors.- Part III: Future theoretical and practical directions.- Conclusions.- Appendix A: Data Collection, Management,Pre-Processing, and Analysis.- Appendix B: Historical and Media Analysis of Wikipedia's Evolutionary Context.- Appendix C: Advantages and Disadvantages of Stepwise Segmented Regression Analysis.