Text Mining with R
The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.
- Learn how to apply the tidy text format to NLP;
- Use sentiment analysis to mine the emotional content of text;
- Identify a document's most important terms with frequency measurements;
- Explore relationships and connections between words with the ggraph and widyr packages;
- Convert back and forth between R's tidy and non-tidy text formats;
- Use topic modeling to classify document collections into natural groups;
- Examine case studies that compare Twitter archives, dig into NASA metadata, and analyze thousands of Usenet messages.
Table of contents
- The Tidy Text Format
- Sentiment Analysis with Tidy Data
- Analyzing Word and Document Frequency: tf-idf
- Relationships Between Words: N-grams and Correlations
- Converting to and from Nontidy Formats
- Topic Modeling
- Case Study: Comparing Twitter Archives
- Case Study: Mining NASA Metadata
- Case Study: Analyzing Usenet Text
| Pages : | 194 |
| Size : | |
| File type : | |
| Downloads: | 105 |
| Created: | 2022-02-03 |
| License: | CC BY-NC-SA |
| Author(s): | Julia Silge, David Robinson |
Others Computer science Tutorials
Asterisk: The Future of Telephony
Others related eBooks about Text Mining with R
Laravel 5 Official DocumentationDownload free course Laravel 5 Official Documentation, pdf file on 1211 pages by Gary Blankenship....
Fundamental Approaches to Software EngineeringDownload free course Fundamental Approaches to Software Engineering, pdf file on 361 pages by Alessandra Russo, Andy Schürr....
MATLAB tutorial in PDFDownload free MATLAB tutorial course in PDF, training file in 34 chapters and 227 pages. Free unaffiliated ebook created from Stack OverFlow contributor....
AlgorithmsDownload free course Algorithms, pdf file on 472 pages by by Jeff Erickson....
Energy Efficient ServersDownload free course Energy Efficient Servers, pdf file on 347 pages by Corey Gough, Ian Steiner, Winston Saunders....
Computational and Inferential Thinking: The Foundations of Data ScienceData Science is about drawing useful conclusions from large and diverse data sets through exploration, prediction, and inference. Our primary tools for exploration are visualizations and descriptive statistics, for prediction are machine learning and optimization, and for inference are statistical t...
Don't Just Roll the DiceDownload free course Don't Just Roll the Dice, pdf file on 74 pages by Neil Davidson....
Learning Regular ExpressionsDownload free course Learning Regular Expressions, pdf file on 94 pages by Stack Overflow Community....
Introduction to Probability, Statistics, and Random ProcessesThis book introduces students to probability, statistics, and stochastic processes. It can be used by both students and practitioners in engineering, various sciences, finance, and other related fields. It provides a clear and intuitive approach to these topics while maintaining mathematical accur...
Category Theory for ProgrammersIn this book, the author illustrates all major concepts of Category Theory using computer code. You are probably aware that functional languages are closer to math than the more popular imperative languages. They also offer more abstracting power. So a natural temptation would be to say: You must le...