Download or read book Big data and machine learning in sociology written by Heinz Leitgöb and published by Frontiers Media SA. This book was released on 2023-06-05 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Social Big Data Mining written by Hiroshi Ishikawa and published by CRC Press. This book was released on 2015-03-25 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the basic concepts and the related technologies of data mining for social medial. Topics include: big data and social data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language processing, social big data applications, and scalability. It explains
Download or read book Big Data in Education written by Ben Williamson and published by SAGE. This book was released on 2017-07-24 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data has the power to transform education and educational research. Governments, researchers and commercial companies are only beginning to understand the potential that big data offers in informing policy ideas, contributing to the development of new educational tools and innovative ways of conducting research. This cutting-edge overview explores the current state-of-play, looking at big data and the related topic of computer code to examine the implications for education and schooling for today and the near future. Key topics include: · The role of learning analytics and educational data science in schools · A critical appreciation of code, algorithms and infrastructures · The rise of ‘cognitive classrooms’, and the practical application of computational algorithms to learning environments · Important digital research methods issues for researchers This is essential reading for anyone studying or working in today′s education environment!
Download or read book Big Data and Social Science written by Ian Foster and published by CRC Press. This book was released on 2020-11-17 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data and Social Science: Data Science Methods and Tools for Research and Practice, Second Edition shows how to apply data science to real-world problems, covering all stages of a data-intensive social science or policy project. Prominent leaders in the social sciences, statistics, and computer science as well as the field of data science provide a unique perspective on how to apply modern social science research principles and current analytical and computational tools. The text teaches you how to identify and collect appropriate data, apply data science methods and tools to the data, and recognize and respond to data errors, biases, and limitations. Features: Takes an accessible, hands-on approach to handling new types of data in the social sciences Presents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposes Illustrates social science and data science principles through real-world problems Links computer science concepts to practical social science research Promotes good scientific practice Provides freely available workbooks with data, code, and practical programming exercises, through Binder and GitHub New to the Second Edition: Increased use of examples from different areas of social sciences New chapter on dealing with Bias and Fairness in Machine Learning models Expanded chapters focusing on Machine Learning and Text Analysis Revamped hands-on Jupyter notebooks to reinforce concepts covered in each chapter This classroom-tested book fills a major gap in graduate- and professional-level data science and social science education. It can be used to train a new generation of social data scientists to tackle real-world problems and improve the skills and competencies of applied social scientists and public policy practitioners. It empowers you to use the massive and rapidly growing amounts of available data to interpret economic and social activities in a scientific and rigorous manner.
Download or read book Big Data and Social Science written by Ian Foster and published by CRC Press. This book was released on 2016-08-10 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
Download or read book Research Handbook on Big Data Law written by Roland Vogl and published by Edward Elgar Publishing. This book was released on 2021-05-28 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: This state-of-the-art Research Handbook provides an overview of research into, and the scope of current thinking in, the field of big data analytics and the law. It contains a wealth of information to survey the issues surrounding big data analytics in legal settings, as well as legal issues concerning the application of big data techniques in different domains.
Download or read book On the path to AI written by Thomas D. Grant and published by Springer Nature. This book was released on 2020-06-02 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two ‘revolutions’ in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of the 19th century. Holmes reconceived law as prophecy based on experience, prefiguring the buzzwords of the machine learning age—prediction based on datasets. On the path to AI introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data, and informs current debates amongst scholars, lawyers and policy makers on how it should be used and regulated wisely. Technologists will also find useful lessons learned from the last 120 years of legal grappling with accountability, explainability, and biased data.
Download or read book Machine Learners written by Adrian Mackenzie and published by MIT Press. This book was released on 2017-11-16 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought? Machine learning—programming computers to learn from data—has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. In this book, Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking. Mackenzie focuses on machine learners—either humans and machines or human-machine relations—situated among settings, data, and devices. The settings range from fMRI to Facebook; the data anything from cat images to DNA sequences; the devices include neural networks, support vector machines, and decision trees. He examines specific learning algorithms—writing code and writing about code—and develops an archaeology of operations that, following Foucault, views machine learning as a form of knowledge production and a strategy of power. Exploring layers of abstraction, data infrastructures, coding practices, diagrams, mathematical formalisms, and the social organization of machine learning, Mackenzie traces the mostly invisible architecture of one of the central zones of contemporary technological cultures. Mackenzie's account of machine learning locates places in which a sense of agency can take root. His archaeology of the operational formation of machine learning does not unearth the footprint of a strategic monolith but reveals the local tributaries of force that feed into the generalization and plurality of the field.
Download or read book Big Data And The Computable Society Algorithms And People In The Digital World written by Domenico Talia and published by World Scientific. This book was released on 2019-03-20 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data and algorithms are changing our life. The awareness of importance and pervasiveness of the digital revolution is the primary element from which to start a path of knowledge to grasp what is happening in the world of big data and digital innovation and to understand these impacts on our minds and relationships between people, traceability and the computability of behavior of individuals and social organizations.This book analyses contemporary and future issues related to big data, algorithms, data analysis, artificial intelligence and the internet. It introduces and discusses relationships between digital technologies and power, the role of the pervasive algorithms in our life and the risk of technological alienation, the relationships between the use of big data, the privacy of citizens and the exercise of democracy, the techniques of artificial intelligence and their impact on the labor world, the Industry 4.0 at the time of the Internet of Things, social media, open data and public innovation.Each chapter raises a set of questions and answers to help the reader to know the key issues in the enormous maze that the tools of info-communication have built around us.
Download or read book Machine Habitus written by Massimo Airoldi and published by John Wiley & Sons. This book was released on 2021-12-13 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: We commonly think of society as made of and by humans, but with the proliferation of machine learning and AI technologies, this is clearly no longer the case. Billions of automated systems tacitly contribute to the social construction of reality by drawing algorithmic distinctions between the visible and the invisible, the relevant and the irrelevant, the likely and the unlikely – on and beyond platforms. Drawing on the work of Pierre Bourdieu, this book develops an original sociology of algorithms as social agents, actively participating in social life. Through a wide range of examples, Massimo Airoldi shows how society shapes algorithmic code, and how this culture in the code guides the practical behaviour of the code in the culture, shaping society in turn. The ‘machine habitus’ is the generative mechanism at work throughout myriads of feedback loops linking humans with artificial social agents, in the context of digital infrastructures and pre-digital social structures. Machine Habitus will be of great interest to students and scholars in sociology, media and cultural studies, science and technology studies and information technology, and to anyone interested in the growing role of algorithms and AI in our social and cultural life.
Download or read book Opportunities and Challenges for Computational Social Science Methods written by Abanoz, Enes and published by IGI Global. This book was released on 2022-03-18 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are living in a digital era in which most of our daily activities take place online. This has created a big data phenomenon that has been subject to scientific research with increasingly available tools and processing power. As a result, a growing number of social science scholars are using computational methods for analyzing social behavior. To further the area, these evolving methods must be made known to sociological research scholars. Opportunities and Challenges for Computational Social Science Methods focuses on the implementation of social science methods and the opportunities and challenges of these methods. This book sheds light on the infrastructure that should be built to gain required skillsets, the tools used in computational social sciences, and the methods developed and applied into computational social sciences. Covering topics like computational communication, ecological cognition, and natural language processing, this book is an essential resource for researchers, data scientists, scholars, students, professors, sociologists, and academicians.
Download or read book Text as Data written by Justin Grimmer and published by Princeton University Press. This book was released on 2022-03-29 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This textual data gives unprecedented insights into fundamental questions in the social sciences, humanities, and industry. Meanwhile new machine learning tools are rapidly transforming the way science and business are conducted. Text as Data shows how to combine new sources of data, machine learning tools, and social science research design to develop and evaluate new insights. Text as Data is organized around the core tasks in research projects using text—representation, discovery, measurement, prediction, and causal inference. The authors offer a sequential, iterative, and inductive approach to research design. Each research task is presented complete with real-world applications, example methods, and a distinct style of task-focused research. Bridging many divides—computer science and social science, the qualitative and the quantitative, and industry and academia—Text as Data is an ideal resource for anyone wanting to analyze large collections of text in an era when data is abundant and computation is cheap, but the enduring challenges of social science remain. Overview of how to use text as data Research design for a world of data deluge Examples from across the social sciences and industry
Download or read book Bit by Bit written by Matthew J. Salganik and published by Princeton University Press. This book was released on 2019-08-06 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This essential guide to doing social research in this fast-evolving digital age explains how the digital revolution is transforming the way social scientists observe behavior, ask questions, run experiments, and engage in mass collaborations.
Download or read book Data Science and Big Data Computing written by Zaigham Mahmood and published by Springer. This book was released on 2016-07-05 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.
Download or read book Research Handbook on Digital Sociology written by Jan Skopek and published by Edward Elgar Publishing. This book was released on 2023-03-02 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring the social implications of digital transformation, as well as demonstrating how we might use digital transformation to further sociological knowledge, this incisive Handbook provides an extensive overview of cutting-edge research on the digital turn of modern society. This title contains one or more Open Access chapters.
Download or read book Emerging Trends in IoT and Integration with Data Science Cloud Computing and Big Data Analytics written by Taser, Pelin Yildirim and published by IGI Global. This book was released on 2021-11-05 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine intelligence, and mobile computing, this book serves professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. It is therefore of most value to data scientists, computer scientists, data analysts, IT specialists, academicians, professionals, researchers, and students working in the field of information and knowledge management in various disciplines that include but are not limited to information and communication sciences, administrative sciences and management, education, sociology, computer science, etc. Moreover, the book provides insights and supports executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.
Download or read book The New Handbook of Political Sociology written by Thomas Janoski and published by Cambridge University Press. This book was released on 2020-03-05 with total page 1412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Political sociology is a large and expanding field with many new developments, and The New Handbook of Political Sociology supplies the knowledge necessary to keep up with this exciting field. Written by a distinguished group of leading scholars in sociology, this volume provides a survey of this vibrant and growing field in the new millennium. The Handbook presents the field in six parts: theories of political sociology, the information and knowledge explosion, the state and political parties, civil society and citizenship, the varieties of state policies, and globalization and how it affects politics. Covering all subareas of the field with both theoretical orientations and empirical studies, it directly connects scholars with current research in the field. A total reconceptualization of the first edition, the new handbook features nine additional chapters and highlights the impact of the media and big data.
