Text Analytics in Marketing: A Practical Guide for Students and Researchers - Daniel Dan,Thomas Reutterer
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This book provides an introduction to text mining and text analytics for marketers, and covers the most important techniques for analyzing, compressing, classifying and visualizing texts and user-generated content (UGC). The methods outlined in this book, focused on using R software, help the reader understand questions such as:Â How can textual data be effectively prepared and manipulated to uncover action ... Full description
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Description
This book provides an introduction to text mining and text analytics for marketers, and covers the most important techniques for analyzing, compressing, classifying and visualizing texts and user-generated content (UGC). The methods outlined in this book, focused on using R software, help the reader understand questions such as:Â How can textual data be effectively prepared and manipulated to uncover actionable marketing insights? How to analyze the impact of UGC in online environments on customer-firm interactions and communications? How to analyze online chatter, likes and dislikes, or any other form of electronic word-of-mouth in relation to brands and competitors? With an ample set of examples, program codes on text mining, and practice examples, this book helps readers, students and marketing managers alike, in addressing their most important questions in learning and practice.Â
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More Information
| Author | Daniel Dan, Thomas Reutterer |
|---|---|
| Publisher | Springer-Verlag GmbH |
| Series | Springer Texts in Business and Economics |
| Release year | 2026 |
| Cover type | Hardcover |
| EAN | 9783032080851 |