Deconstructing what machine learning does when processing text

Three themes are of growing importance in the field of data analysis: the demand to process large quantities of open-ended text, the growth in the use of open-source tools, and a need to understand what it is that we do when we utilise computational text analytics.

Introduction

These notes are provided to support the interactive session to be conducted by Ray Poynter at the ESOMAR Fusion Conference in Madrid, Spain, in November 2019. The purpose of these notes is to provide some key background information relating to the programming language R and to the elements of the text analytics that will be explored interactively.

This paper brings together three themes that are of growing importance:

  1. The demand to process large quantities of open-ended text;
  2. The growth in the use of open-source tools, such as Python and R;
  3. A need to understand what it is that we...

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