Idioma: Inglés
Publicado por Cambridge University Press, 1999
ISBN 10: 0521645573 ISBN 13: 9780521645577
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Añadir al carritoCondición: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: SOME ] [ Edition: second ] Publisher: Cambridge University Press Pub Date: 6/13/1999 Binding: Paperback Pages: 400 second edition.
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Idioma: Inglés
Publicado por Walter De Gruyter Feb 2026, 2026
ISBN 10: 311068067X ISBN 13: 9783110680676
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Añadir al carritoBuch. Condición: Neu. Neuware - Society is changing it is becoming more diverse and digital. Social media today plays a central role in human communication. With a changing society, the way social scientists analyze it is also evolving. In recent years, it has become significantly more difficult to encourage people to participate in surveys. Furthermore, digitization opens up data options that go beyond the survey method. Information published online represents valuable digital behavioral traces and provides social researchers with another important source of data alongside their scientific surveys, which in recent years have increasingly been conducted online.Computational methods have played a central role in social research from the very beginning. This applies today more than ever to data analysis, but now also to data collection. The increasing attention paid to machine learning methods in the statistical analysis of social science data represents a further remarkable development in the analysis of social science data.This textbook addresses these developments and familiarizes readers with both elementary and more advanced methods of data analysis. Fundamentals and techniques of data management, programming with R, statistical data analysis, descriptive and causal inference, as well as predictive modeling are covered in depth. All methods are exemplified using real data either from survey research, the social media platform Bluesky or a large digital newspaper archive. Thematically, these data are focused on current sociological topics, particularly those related to human happiness, energy transition and climate policy, AI, political attitudes and the rise in right-wing voting.Data science encompasses more than the algorithms required for data analysis and statistical learning. No less relevant are the rules by which social research and data analysis are conducted, data quality is ensured, and the results are validated. This textbook aims to provide this overview.
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Añadir al carritoBuch. Condición: Neu. Data Science in Social Research | An Applied Guide to Statistical and Computational Methods with R | Uwe Engel (u. a.) | Buch | XI | Englisch | 2026 | Walter de Gruyter | EAN 9783110680676 | Verantwortliche Person für die EU: Walter de Gruyter GmbH, De Gruyter GmbH, Genthiner Str. 13, 10785 Berlin, productsafety[at]degruyterbrill[dot]com | Anbieter: preigu.
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Añadir al carritoCondición: Sehr gut. Zustand: Sehr gut | Seiten: 467 | Sprache: Englisch | Produktart: Bücher | The emergent field of CSS is growing in scientific importance and public interest. There is no doubt that the field of social science needs to keep up with a rapidly changing society; the ubiquity of digital media in all aspects of life, work, play, and leisure is requiring new perspectives and theories. Driving forces include technological advancements in computer systems, the rise of machine learning, and the ubiq-uity of artificial intelligence. Digital media are being adopted on a large scale globally, leading to the creation and collection of vast amounts of structured and unstructured data. This holds the promise of a new type of open science, where data in the social sciences is a public good instead of serving commercial interests. These developments affect both the objects of social-science research as well as its methods. We are witnessing a paradigm shift from traditional survey research to large-scale computational methods, not least because of the mere availability of large amount of digital trace data. This shift has concrete implications such as usage of disparate kinds of data (e.g., unstructured data), application of new types of methods (e.g., machine learning), exposition to a wide range of threats to data quality and valida-tion, and finally different inferential paradigms. The goal of this textbook is to respond to this paradigm shift with an exposition of computational methods required to conduct social research in the digital age. Five basic points characterize the in-tended scope and focus of the textbook: Selection of methods, Data quality, Statistical learning & validation, Artificial intelligence and Balance of statistical foundations and programming.
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Idioma: Inglés
Publicado por Springer-Verlag New York Inc, 2015
ISBN 10: 3319179950 ISBN 13: 9783319179957
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 2015 edition. 432 pages. 9.25x6.10x0.94 inches. In Stock.
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Añadir al carritoTaschenbuch. Condición: Neu. Advanced Computational Methods for Knowledge Engineering | Proceedings of 3rd International Conference on Computer Science, Applied Mathematics and Applications - ICCSAMA 2015 | Hoai An Le Thi (u. a.) | Taschenbuch | xiv | Englisch | 2015 | Springer | EAN 9783319179957 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer International Publishing, Springer International Publishing, 2015
ISBN 10: 3319179950 ISBN 13: 9783319179957
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume contains the extended versions of papers presented at the 3rd International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2015) held on 11-13 May, 2015 in Metz, France. The book contains 5 parts: 1. Mathematical programming and optimization: theory, methods and software, Operational research and decision making, Machine learning, data security, and bioinformatics, Knowledge information system, Software engineering. All chapters in the book discuss theoretical and algorithmic as well as practical issues connected with computation methods & optimization methods for knowledge engineering and machine learning techniques.
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Añadir al carritoCondición: Gut. Zustand: Gut | Seiten: 444 | Sprache: Englisch | Produktart: Bücher | The proceedings consists of 30 papers which have been selected and invited from the submissions to the 2nd International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2014) held on 8-9 May, 2014 in Budapest, Hungary. The conference is organized into 7 sessions: Advanced Optimization Methods and Their Applications, Queueing Models and Performance Evaluation, Software Development and Testing, Computational Methods for Mobile and Wireless Networks, Computational Methods for Knowledge Engineering, Logic Based Methods for Decision Making and Data Mining and Nonlinear Systems and Applications, respectively. All chapters in the book discuss theoretical and practical issues connected with computational methods and optimization methods for knowledge engineering. The editors hope that this volume can be useful for graduate and Ph.D. students and researchers in Computer Science and Applied Mathematics. It is the hope of the editors that readers of this volume can find many inspiring ideas and use them to their research. Many such challenges are suggested by particular approaches and models presented in individual chapters of this book.
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Añadir al carritoCondición: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | These proceedings consist of 19 papers, which have been peer-reviewed by international program committee and selected for the 5th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2017), which was held on June 30¿July 1, 2017 in Berlin, Germany. The respective chapters discuss both theoretical and practical issues in connection with computational methods and optimization methods for knowledge engineering. The broad range of application areas discussed includes network computing, simulation, intelligent and adaptive e-learning, information retrieval, sentiment analysis, autonomous underwater vehicles, social media analysis, natural language processing, biomimetics in organizations, and cash management. In addition to pure content, the book offers many inspiring ideas and suggests new research directions, making it a valuable resource for graduate students, Ph.D. students, and researchers in Computer Science and Applied Mathematics alike.
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