Description
| Product ID: | 9781544390000 |
| Product Form: | Paperback / softback |
| Country of Manufacture: | US |
| Series: | Quantitative Applications in the Social Sciences |
| Title: | Analyzing Textual Information |
| Subtitle: | From Words to Meanings through Numbers |
| Authors: | Author: Johannes Ledolter, Lea Vandervelde |
| Page Count: | 192 |
| Subjects: | Research methods: general, Research methods: general, Social research and statistics, Political science and theory, Social research & statistics, Political science & theory |
| Description: | Select Guide Rating 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 are available on an accompanying website for the book. 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. 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. |
| Imprint Name: | SAGE Publications Inc |
| Publisher Name: | SAGE Publications Inc |
| Country of Publication: | GB |
| Publishing Date: | 2021-07-13 |
