Ebook

Using Machine Learning to Automate Text Coding White Paper

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We are all in a state of information overload with people communicating digitally more than ever whether it’s analyzing tweets, reviews, or open-ended responses from a survey. This gold mine of untapped insights then needs to be cleaned and processed before you can conduct your analysis. This is both time consuming and a huge pain for researchers and analysts.

For the last 20 years, the survey research industry has waited with bated breath for text analysis technologies to transform the way we analyze text data. In the last year or so, technology has reached a point where they can work with a high level of accuracy.

What you'll get from this ebook

Find out how to easily extract useful insight from text data so you cut your analysis time in half and most importantly optimize your customer experience.

  • Automated text analysis in market research
  • Methodology
  • Results
  • Productivity

More about this ebook

This ebook presents a case study illustrating how automated categorization can be used to dramatically improve the productivity of categorizing text data, compared to manual categorization (i.e., “coding”). The case study shows that the gain in productivity was at least 134%, and arguably much higher. The resulting categorization has accuracy at a level that would be expected if a subject matter expert had manually performed the categorization.

This study should not be regarded as being representative. Some data sets are inevitably more suited to automatic categorization than others, and such decisions should be made on a case-by-case basis. This ebook illustrates how to make such a decision.

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