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Text Analytics for Business Decisions

Frontmatter

Contents

Preface

Chapter 1 Framing Analytical Questions

Chapter 2 Analytical Tool Sets

Chapter 3 Text Data Sources and Formats

Chapter 4 Preparing the Data File

Chapter 5 Word Frequency Analysis

Chapter 6 Keyword Analysis

Chapter 7 Sentiment Analysis

Chapter 8 Visualizing Text Data

Chapter 9 Coding Text Data

Chapter 10 Named Entity Recognition

Chapter 11 Topic Recognition in Documents

Chapter 12 Text Similarity Scoring

Chapter 13 Analysis of Large Datasets by Sampling

Chapter 14 Installing R and RStudio

Chapter 15 Installing the Entity Extraction Tool

Chapter 16 Installing the Topic Modeling Tool

Chapter 17 Installing the Voyant Text Analysis Tool

Index

TABD.zip

With the rise in data science development, we now have many remarkable techniques and tools to extend data analysis from numeric and categorical data to textual data. Sifting through the open-ended responses from a survey, for example, was an arduous process when performed by hand. Using a case study approach, this book was written for business analysts who wish to increase their skills in extracting answers for text data in order to support business decision making. Most of the exercises use Excel, today’s most common analysis tool, and R, a popular analytic computer environment.

With the rise in data science development, we now have many remarkable techniques and tools to extend data analysis from numeric and categorical data to...

Format

Text Analytics for Business Decisions

A Case Study Approach

Andres Fortino

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