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This title discusses 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 also proposes a future research agenda related to these issues—with the ultimate goal of shaping 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. Roles, Trust, and Reputation in Social Media Knowledge Markets exposes issues that have not been satisfactorily dealt with in the current literature. 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 here 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.

Physics. --- Complex Networks. --- Data Mining and Knowledge Discovery. --- Complex Systems. --- Methodology of the Social Sciences. --- Computer Appl. in Social and Behavioral Sciences. --- Data mining. --- Social sciences --- Physique --- Exploration de données (Informatique) --- Sciences sociales --- Data processing. --- Methodology. --- Informatique --- Méthodologie --- Social sciences_xData processing. --- Social sciences_xMethodology. --- Physics --- Physical Sciences & Mathematics --- Physics - General --- Knowledge, Sociology of. --- Social media. --- Knowledge, Theory of (Sociology) --- Sociology of knowledge --- User-generated media --- Application software. --- System theory. --- Social sciences. --- Communication --- User-generated content --- Knowledge, Theory of --- Public opinion --- Sociology --- Social epistemology --- Applications of Graph Theory and Complex Networks. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Systems, Theory of --- Systems science --- Science --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics --- Philosophy

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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. .

Human rights --- Information systems --- grafentheorie --- IoT (Internet of Things) --- big data --- computers --- ethiek --- systeemtheorie --- database management --- fysica --- computerkunde --- data acquisition

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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.

Computer science. --- Social media. --- Big data. --- Data mining. --- Mass media. --- Communication. --- Social sciences in mass media. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Media Sociology. --- Social Media. --- Communication Studies. --- Big Data/Analytics. --- Applications of Graph Theory and Complex Networks. --- Communication, Primitive --- Mass communication --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Data sets, Large --- Large data sets --- User-generated media --- Informatics --- Media, Mass --- Media, The --- Mass media --- Sociology --- Communication --- Database searching --- User-generated content --- Science --- Social media --- Data sets --- Physics. --- Natural philosophy --- Philosophy, Natural --- Physical sciences --- Dynamics

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Digital and social media companies such as Apple, Google, and Facebook grip the globe with market, civic, and political strength akin to large, sovereign states. Yet, these corporations are private entities. How should states and communities protect the individual rights of their citizens - or their national and local interests - while keeping pace with globalized digital companies? This scholarly compendium examines regulatory solutions which encourage content diversity and protect fundamental rights. The volume compares European and US regulatory approaches, including closer focus on topics such as privacy, copyright, and freedom of expression. Further, we propose pedagogical models for educating students on possible regulatory regimes of the future. Our final chapter invites readers to consider social and digital media regulation for both this generation and the ones to come.

Mass communications --- mediarecht --- sociale media --- massacommunicatie --- massamedia --- media-ethiek --- Europe --- United States of America --- Internet --- Digital media --- Law and legislation

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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.

Computer science. --- Big data. --- Research --- Data mining. --- Application software. --- Bioinformatics. --- Computer Science. --- Data Mining and Knowledge Discovery. --- Big Data/Analytics. --- Computer Appl. in Social and Behavioral Sciences. --- Research Ethics. --- Moral and ethical aspects. --- Data warehousing. --- Data sets, Large --- Large data sets --- Information warehousing --- Warehousing, Data --- Database management --- Management information systems --- Multidimensional databases --- Social sciences --- Research-Moral and ethical aspec. --- Data processing. --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Data sets --- Data processing --- Research ethics --- Research—Moral and ethical aspects. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software