Analyzing Textual Information From Words to Meanings through Numbers

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Author: Johannes Ledolter
Publisher: SAGE Publications Inc
Edition: 1st Edition
ISBN-13: 9781544390000
Publishing year: 2021-05-01
No of pages: 192 pages
Weight: 240 grm
Language: English
Book binding: Paperback

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JOHANNES LEDOLTER has professorships in both the Business School, where he is Robert Thomas Holmes Professor of Business Analytics, and in the Department of Statistics and Actuarial Science at the University of Iowa. He is a Fellow of the American Statistical Association and the American Society for Quality, and Elected Member of the International Statistical Institute. He is the author of several books, including Statistical Methods for Forecasting, Introduction to Regression Modeling, Testing 1-2-3: Experimental Design with Applications in Marketing and Service Operations, and Data Mining and Business Analytics with R. He was Professor of Statistics at the Vienna University of Economics and Business from 1997 to 2015, and held visiting professorships at Princeton, Yale, Stanford and the University of Chicago. Since 2011, he has been Associate Investigator at the Center for Prevention and Treatment of Vision Loss at the Iowa City VA Health Care System, which studies optic nerve and retinal disorders in relation to traumatic brain injury. Professor Ledolter enjoys working on multi-disciplinary projects that involve both numeric and text information.

Researchers in the social sciences and beyond are dealing more and more with massive quantities of text data requiring analysis, from historical letters to the constant stream of content in social media. Traditional texts on statistical analysis have focused on numbers, but this book will provide a practical introduction to the quantitative analysis of textual data. Using up-to-date R methods, this book will take readers through the text analysis process, from text mining and pre-processing the text to final analysis. It includes two major case studies using historical and more contemporary text data to demonstrate the practical applications of these methods. Currently, there is no introductory how-to book on textual data analysis with R that is up-to-date and applicable across the social sciences. Code and a variety of additional resources to enrich the use of this book are available on an accompanying website at: https://www.biz.uiowa.edu/faculty/jledolter/analyzing-textual-information/. These resources include data files from the 39th Congress, and also the collection of tweets of President Trump, now no longer available to researchers via Twitter itself.