
Quantitative Text Analysis Using R
Description
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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.
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Persons
Anna Wohlmann is a doctoral candidate at the Technical University of Munich, holding a Master's degree in Politics & Technology from the Technical University of Munich and a Bachelor's degree in Political Science with a minor in Psychology from the University of Mannheim. When introduced to QTA with R in a bachelor-seminar, Anna immediately knew this would be their method of choice. The analysis of social media content created by social movements is the main focus of Annas research.
Content
Chapter 2: Using R for Text Analysis
Chapter 3: Text as Data: Obtaining, Preparing, and Cleaning
Chapter 4: Extracting and Visualising Information from Text
Chapter 5: Supervised Machine Learning for Text Data
Chapter 6: Unsupervised Machine Learning for Text Data
Chapter 7: Evaluation and Validation of Quantitative Text Analysis
Chapter 8: Using Python within R for QTA
Chapter 9: Communicating Text Analysis
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
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