The book proposes a systematic approach to big data collection, documentation and development of analytic procedures that foster collaboration on a large scale. This approach, designated as "data factoring" emphasizes the need to think of each individual dataset developed by an individual project as part of a broader data ecosystem, easily accessible and exploitable by parties not directly involved with data collection and documentation. Furthermore, data factoring uses and encourages pre-analytic operations that add value to big data sets, especially recombining and repurposing.
The book proposes a research-development agenda that can undergird an ideal data factory approach. Several programmatic chapters discuss specialized issues involved in data factoring (documentation, meta-data specification, building flexible, yet comprehensive data ontologies, usability issues involved in collaborative tools, etc.). The book also presents case studies for data factoring and processing that can lead to building better scientific collaboration and data sharing strategies and tools.
Finally, the book presents the teaching utility of data factoring and the ethical and privacy concerns related to it.
Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com
The volume presents, in a synergistic manner, significant theoretical and practical contributions in the area of social media reputation and authorship measurement, visualization, and modeling. The book justifies and proposes contributions to a future agenda for understanding the requirements for making social media authorship more transparent. Building on work presented in a previous volume of this series, Roles, Trust, and Reputation in Social Media Knowledge Markets, this book discusses new tools, applications, services, and algorithms that are needed for authoring content in a real-time publishing world. These insights may help people who interact and create content through social media better assess their potential for knowledge creation. They may also assist in analyzing audience attitudes, perceptions, and behavior in informal social media or in formal organizational structures. In addition, the volume includes several chapters that analyze the higher order ethical, critical thinking, and philosophical principles that may be used to ground social media authorship. Together, the perspectives presented in this volume help us understand how social media content is created and how its impact can be evaluated.The chapters demonstrate thought leadership through new ways of constructing social media experiences and making traces of social interaction visible. Transparency in Social Media aims to help researchers and practitioners design services, tools, or methods of analysis that encourage a more transparent process of interaction and communication on social media. Knowing who has added what content and with what authority to a specific online social media project can help the user community better understand, evaluate and make decisions and, ultimately, act on the basis of such information.
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 the crucial 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.
Knowledge and expertise, especially of the kind that can shape public opinion, have been traditionally the domain of individuals holding degrees awarded by higher learning institutions or occupying formal positions in notable organizations. Expertise is validated by reputations established in an institutionalized marketplace of ideas with a limited number of "available seats" and a stringent process of selection and retention of names, ideas, topics and facts of interest. However, the social media revolution, which has enabled over two billion Internet users not only to consume, but also to produce information and knowledge, has created a secondary and very active informal marketplace of ideas and knowledge. Anchored by platforms like Wikipedia, YouTube, Facebook and Twitter, this informal marketplace has low barriers to entry and has become a gigantic and potentially questionable, knowledge resource for the public at large. Roles, Trust and Reputation in Social Media Knowledge Markets will discuss some of the emerging trends in defining, measuring and operationalizing reputation as a new and essential component of the knowledge that is generated and consumed online. The book will propose a future research agenda related to these issues. The ultimate goal of research agenda being to shape the next generation of theoretical and analytic strategies needed for understanding how knowledge markets are influenced by social interactions and reputations built around functional roles. The authors, including leading scholars and young innovators, will share with the readers some of the main lessons they have learned from their own work in these areas and will discuss the issues, topics and sub-areas that they find under-studied or that promise the greatest intellectual payoff in the future. The discussion will be placed in the context of social network analysis and "big data" research. Roles, Trust and Reputation in Social Media Knowledge Markets exposes issues that have not been satisfactorily dealt with in the current literature, as the research agenda in reputation and authorship is still emerging. In a broader sense, the volume aims to change the way in which knowledge generation in social media spaces is understood and utilized. The tools, theories and methodologies proposed by the contributors offer concrete avenues for developing the next generation of research strategies and applications that will help: tomorrow's information consumers make smarter choices, developers to create new tools and researchers to launch new research programs.
This book springs from a multidisciplinary, multi-organizational, and multi-sector conversation about the privacy and ethical implications of research in human affairs using big data. The need to cultivate and enlist the public's trust in the abilities of particular scientists and scientific institutions constitutes one of this book's major themes. The advent of the Internet, the mass digitization of research information, and social media brought about, among many other things, the ability to harvest - sometimes implicitly - a wealth of human genomic, biological, behavioral, economic, political, and social data for the purposes of scientific research as well as commerce, government affairs, and social interaction. What type of ethical dilemmas did such changes generate? How should scientists collect, manipulate, and disseminate this information? The effects of this revolution and its ethical implications are wide-ranging. This book includes the opinions of myriad investigators, practitioners, and stakeholders in big data on human beings who also routinely reflect on the privacy and ethical issues of this phenomenon. Dedicated to the practice of ethical reasoning and reflection in action, the book offers a range of observations, lessons learned, reasoning tools, and suggestions for institutional practice to promote responsible big data research on human affairs. It caters to a broad audience of educators, researchers, and practitioners. Educators can use the volume in courses related to big data handling and processing. Researchers can use it for designing new methods of collecting, processing, and disseminating big data, whether in raw form or as analysis results. Lastly, practitioners can use it to steer future tools or procedures for handling big data. As this topic represents an area of great interest that still remains largely undeveloped, this book is sure to attract significant interest by filling an obvious gap in currently available literature.