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Quantitative Text Analysis Using R by Julian Bernauer
Grounded in examples from across the social sciences, this book walks you through the process of doing quantitative text analysis step by step. Clear and accessible, it empowers you to progress from beginner level to understanding and using computational social science concepts with ease. Covering key steps in the research process like ethics, data collection and model choice, it helps you develop important research skills - and equips you with the programming tools you need to handle text data without error.
The textbook offers R software guidance at an easy-to-follow pace, the book presents the coding skills you need to collect and prepare data, providing a strong foundation as you move into data analysis. It will:
· Help you develop key data skills like cleaning, managing, classifying and visualizing data
· Encourage your ability to be critical and reflective when dealing with data
· Offer clear guidance on using messy, real-world data and big data from sources like Wikipedia
Supported by practical online resources including extensive coding examples and software guidance, this book will give you confidence in applying your programming skills and enable you to take control of handling textual data in your own research.
About the Author: Julian Bernauer is a Researcher and permanent Scientific Staff at the Mannheim Centre of European Social Research (MZES), University of Mannheim. His interest in QTA started in 2006, when he wrote a master thesis supervised by Prof. Thomas Bräuninger at the University of Konstanz (where he studied Politics and Public Management) analysing speeches of members of the German parliament. The topic of this research and his doctoral studies at the University of Konstanz (finished in 2012) was political representation of different sorts, and he moved on to lecture and study comparative political institutions as a Postdoctoral Researcher and Lecturer (Oberassistent) at the University of Bern. Since 2017, he is a member of the Mannheim Centre of European Social Research (MZES), first as staff in the Data and Methods Unit (DMU), and since 2020 as permanent Scientific Staff and Researcher in the institute′s IT department. He is also involved in the management of the MZES.
Number of pages | 232 |
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