Meer dan een miljoen boeken binnen handbereik!
Bookbot

Ian Foster

    The image of the Habsburg army in Austrian prose fiction 1888 to 1914
    Big Data and Social Science
    Arthur Schnitzler: Zeitgenossenschaften, contemporaneities
    • Arthur Schnitzler durchlebte eine Zeitenwende: der Erste Weltkrieg verwandelte Österreich von einem multinationalen Imperium in einen deutschsprachigen Kleinstaat. Beides, das Vorher und das Nachher, markiert Schnitzlers Zeitgenossenschaft. Er lebte in einer geistesgeschichtlichen und literarischen Umbruchsphase. Der bürgerlich-liberale Konsens, der Schnitzlers Milieu charakterisierte, wurde in seinen Grundüberzeugungen herausgefordert. Wissenschaftliche und technische Errungenschaften kennzeichnen Schnitzlers Zeitgenossenschaft. Arthur Schnitzler lived through a time of profound political, social and intellectual change: the First World War transformed Austria from a huge multinational empire into a small Alpine republic; the liberal middle-class consensus which characterised the author’s personal background began to disintegrate during this time, and new departures not only in science and technology but also in literary styles and conventions posed new challenges to a politically involved and acutely socially aware modern writer.

      Arthur Schnitzler: Zeitgenossenschaften, contemporaneities
    • Big Data and Social Science

      A Practical Guide to Methods and Tools

      • 376bladzijden
      • 14 uur lezen

      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.

      Big Data and Social Science