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 The Wiley Blackwell Companion to Sociology written by George Ritzer and published by John Wiley & Sons. This book was released on 2016-09-26 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring a collection of original chapters by leading and emerging scholars, The Wiley-Blackwell Companion to Sociology presents a comprehensive and balanced overview of the major topics and emerging trends in the discipline of sociology today. Features original chapters contributed by an international cast of leading and emerging sociology scholars Represents the most innovative and 'state-of-the-art' thinking about the discipline Includes a general introduction and section introductions with chapters summaries by the editor
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 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 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 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 A Journey of Discovering Sociology written by Long Chen and published by Springer Nature. This book was released on 2020-08-13 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the author’s interviews with twenty leading sociologists from various fields at nine different prestigious universities in the USA, including their viewpoints, anecdotes and experiences in the world of sociology. Each chapter presents an interview with one sociologist, covering their views on contemporary sociology, their early university experiences, teaching experiences, experiences with publishing, and their reflections on life as a sociologist. Through the dialogues, readers can learn about sociology as well as sociologists’ lives in a unique and insightful way – just as the author did – and embark on a journey of discovering sociology. The book helps readers find their own answers to the two main questions explored: “What is sociology?” and “What is a sociologist’s life like?”
Download or read book Data Science and Social Research written by N. Carlo Lauro and published by Springer. This book was released on 2017-11-17 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume lays the groundwork for Social Data Science, addressing epistemological issues, methods, technologies, software and applications of data science in the social sciences. It presents data science techniques for the collection, analysis and use of both online and offline new (big) data in social research and related applications. Among others, the individual contributions cover topics like social media, learning analytics, clustering, statistical literacy, recurrence analysis and network analysis. Data science is a multidisciplinary approach based mainly on the methods of statistics and computer science, and its aim is to develop appropriate methodologies for forecasting and decision-making in response to an increasingly complex reality often characterized by large amounts of data (big data) of various types (numeric, ordinal and nominal variables, symbolic data, texts, images, data streams, multi-way data, social networks etc.) and from diverse sources. This book presents selected papers from the international conference on Data Science & Social Research, held in Naples, Italy in February 2016, and will appeal to researchers in the social sciences working in academia as well as in statistical institutes and offices.
Download or read book Sociological Foundations of Computational Social Science written by Yoshimichi Sato and published by Springer Nature. This book was released on with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Sociological Science written by Gërxhani, Klarita and published by Edward Elgar Publishing. This book was released on 2022-06-10 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: 22 out of the 26 Chapters will be available Open Access on Elgaronline when the book is published. The Handbook of Sociological Science offers a refreshing, integrated perspective on research programs and ongoing developments in sociological science. It highlights key shared theoretical and methodological features, thereby contributing to progress and cumulative growth of sociological knowledge.
Download or read book Routledge International Handbook of the Sociology of Art and Culture written by Laurie Hanquinet and published by Routledge. This book was released on 2015-09-16 with total page 718 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Routledge Handbook of the Sociology of Arts and Culture offers a comprehensive overview of sociology of art and culture, focusing especially – though not exclusively – on the visual arts, literature, music, and digital culture. Extending, and critiquing, Bourdieu’s influential analysis of cultural capital, the distinguished international contributors explore the extent to which cultural omnivorousness has eclipsed highbrow culture, the role of age, gender and class on cultural practices, the character of aesthetic preferences, the contemporary significance of screen culture, and the restructuring of popular culture. The Handbook critiques modes of sociological determinism in which cultural engagement is seen as the simple product of the educated middle classes. The contributions explore the critique of Eurocentrism and the global and cosmopolitan dimensions of cultural life. The book focuses particularly on bringing cutting edge ‘relational’ research methodologies, both qualitative and quantitative, to bear on these debates. This handbook not only describes the field, but also proposes an agenda for its development which will command major international interest.
