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"This ambitious sweep through data science techniques provides an invaluable introduction to the toolbox of big data methodologies, as applied to social science data. It provides tremendous value not only to beginners in the field, but also to experienced data scientists wishing to round out their knowledge of this broad and dynamic field."- Kenneth Benoit, Department of Methodology, London School of Economics and Political Science, UK"...one of the very best 'how-to' books on big data that researchers, enterprise analysts, and government practitioners will find equally valuable...takes the reader along a near-perfect path to understanding the fundamental elements of constructing a practical and realistic model for Big Data Analysis that any organization can execute by simply following the path outlined in this book...one of those books that every research group and data-analysis team will want to have on their reference shelf."- Tom Herzog, Former Deputy Commissioner, NY State Department of Corrections and Community Supervision, USABig 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.FeaturesTakes an accessible, hands-on approach to handling new types of data in the social sciencesPresents the key data science tools in a non-intimidating way to both social and data scientists while keeping the focus on research questions and purposesIllustrates social science and data science principles through real-world problemsLinks computer science concepts to practical social science researchPromotes good scientific practiceProvides freely available data and code as well as practical programming exercises through Binder and GitHubNew to the Second EditionIncreased use of examples from different areas of social sciencesNew chapter on dealing with Bias and Fairness in Machine Learning modelsExpanded chapters focusing on Machine Learning and Text AnalysisRevamped hands-on Jupyter notebooks to reinforce concepts covered in each chapterThis 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.Diese Arbeit analysiert die voelkerrechtlichen Menschenrechtsgewahrleistungen und ihre verschiedenen Instrumente zur verfahrensrechtlichen Durchsetzbarkeit. Diese verfahrensrechtlichen Instrumentarien beziehen zunehmend das Individuum in den Prozess der Rechtsbeachtung und Rechtsbewahrung auf Voelkerrechtsebene ein, wie zum Beispiel das Individualbeschwerdeverfahren vor dem Europaischen Gerichtshof fur Menschenrechte verdeutlicht. Im Rahmen der Arbeit wird untersucht, ob dieses Phanomen des Einbezugs des Individuums in den Prozess der Rechtsdurchsetzung im voelkerrechtlichen Menschenrechtsschutz auf den europaischen Rechtsraum begrenzt ist, oder ob es Tendenzen gibt, dass dem Individuum im voelkerrechtlichen Menschenrechtsschutz generell zunehmend Verfahrenspositionen eingeraumt werden. In diesem Zusammenhang widmet sich die Untersuchung schliesslich der Frage, ob und inwieweit von einer Stellung des Individuums im voelkerrechtlichen Menschenrechtsschutz, d. h. von einer Voelkerrechtssubjektivitat des Einzelnen, gesprochen werden kann.
