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  • MPI Bildungsforschung  (5)
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  • 1
    UID:
    b3kat_BV046991789
    Format: xv, 390 Seiten , Illustrationen, Diagramme
    Edition: First edition
    ISBN: 9780525574514 , 9780593238745
    Content: "Social media connected the world--and gave rise to fake news and increasing polarization. Now a leading researcher at MIT draws on 20 years of research to show how these trends threaten our political, economic, and emotional health in this eye-opening exploration of the dark side of technological progress. Today we have the ability, unprecedented in human history, to amplify our interactions with each other through social media. It is paramount, MIT social media expert Sinan Aral says, that we recognize the outsized impact social media has on our culture, our democracy, and our lives in order to steer today's social technology toward good, while avoiding the ways it can pull us apart. Otherwise, we could fall victim to what Aral calls "The Hype Machine." As a senior researcher of the longest-running study of fake news ever conducted, Aral found that lies spread online farther and faster than the truth--a harrowing conclusion that was featured on the cover of Science magazine. Among the questions Aral explores following twenty years of field research: Did Russian interference change the 2016 election? And how is it affecting the vote in 2020? Why does fake news travel faster than the truth online? How do social ratings and automated sharing determine which products succeed and fail? How does social media affect our kids? First, Aral links alarming data and statistics to three accelerating social media shifts: hyper-socialization, personalized mass persuasion, and the tyranny of trends. Next, he grapples with the consequences of the Hype Machine for elections, businesses, dating, and health. Finally, he maps out strategies for navigating the Hype Machine, offering his singular guidance for managing social media to fulfill its promise going forward. Rarely has a book so directly wrestled with the secret forces that drive the news cycle every day"--
    Note: Pandemics, Promise, and Peril -- The New Social Age -- The End of Reality -- The Hype Machine -- Your Brain on Social Media -- A Network's Gravity is Proportional to Its Mass -- Personalized Mass Persuasion -- Hypersocialization -- Strategies for a Hypersocialized World -- The Attention Economy and the Tyranny of Trends -- The Wisdom and Madness of Crowds -- Social Media's Promise Is Also Its Peril -- Building a Better Hype Machine
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-0-525-57452-1
    Language: English
    Subjects: General works , Sociology
    RVK:
    RVK:
    Keywords: Social Media ; Informationsgesellschaft ; Propaganda ; Fehlinformation
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    gbv_553087401
    Format: 1 Online-Ressource ([6], 506 [i.e. 509] p)
    Edition: Ann Arbor, Mich UMI 1999 Electronic reproduction; Digital version of: (Early English books, 1641-1700 ; 1249:4 and 1791:18)
    Series Statement: Early English Books Online / EEBO
    Content: eebo-0216
    Note: Reproductions of originals in the Henry E. Huntington Library and Art Gallery and British Library , Wing (2nd ed., 1994), B3824D , Formerly identified as Wing C464 (number cancelled); Wing (2nd ed., 1994) attributes this work to Dominique Bouhours and assigns number B3824D , Electronic reproduction; Digital version of: (Early English books, 1641-1700 ; 1249:4 and 1791:18)
    Language: English
    URL: Volltext  (Deutschlandweit zugänglich)
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  • 3
    Online Resource
    Online Resource
    New Haven : Yale University Press
    UID:
    gbv_166985938X
    Format: 1 online resource (312 pages)
    ISBN: 9780300244854
    Series Statement: The Margellos World Republic of Letters Ser.
    Content: Cover -- Half Title -- Title -- Copyright -- Dedication -- Beginnings -- Endings -- Notes.
    Note: Description based on publisher supplied metadata and other sources
    Additional Edition: ISBN 9780300228946
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9780300228946
    Language: English
    Subjects: Comparative Studies. Non-European Languages/Literatures
    RVK:
    URL: Cover
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  • 4
    UID:
    gbv_1670675963
    Format: 310 p
    Edition: 1st ed.
    ISBN: 9781787286474 , 9781787287600
    Content: Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization.
    Note: Includes bibliographical references and index
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : PACKT Publishing
    UID:
    gbv_1670676234
    Format: 389 p
    Edition: 1st ed.
    ISBN: 9781785887918 , 9781785888922
    Content: Learn the techniques and math you need to start making sense of your data About This Book • Enhance your knowledge of coding with data science theory for practical insight into data science and analysis • More than just a math class, learn how to perform real-world data science tasks with R and Python • Create actionable insights and transform raw data into tangible value Who This Book Is For You should be fairly well acquainted with basic algebra and should feel comfortable reading snippets of R/Python as well as pseudo code. You should have the urge to learn and apply the techniques put forth in this book on either your own data sets or those provided to you. If you have the basic math skills but want to apply them in data science or you have good programming skills but lack math, then this book is for you. What You Will Learn • Get to know the five most important steps of data science • Use your data intelligently and learn how to handle it with care • Bridge the gap between mathematics and programming • Learn about probability, calculus, and how to use statistical models to control and clean your data and drive actionable results • Build and evaluate baseline machine learning models • Explore the most effective metrics to determine the success of your machine learning models • Create data visualizations that communicate actionable insights • Read and apply machine learning concepts to your problems and make actual predictions In Detail Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you'll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas. With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you'll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You'll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means. Style and approach This is an easy-to-understand and accessible tutorial. It is a step-by-step guide with use cases, examples, and illustrations to get you well-versed with the concepts of data science. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.
    Note: Includes bibliographical references and index
    Language: English
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