Research Methodologies

April 21, 2017

2 min read

Using Text Analytics to Tidy a Word Cloud

The trick to a great word cloud is to first tidy up the raw text using automated text analytics.

By Tim Bock

It is common when people create word clouds that they want more control. Limit the word cloud to frequently occurring words. Join together words in phrases. Automatically group together words that have the same meaning. The trick to doing this is to first tidy up the raw text using automated text analytics. Then, create the word cloud using the tidied text.

Why don’t people like Tom Cruise?

In my earlier post, I explained how you can create and interactively modify word clouds in Displayr using an example about why people dislike Tom Cruise. In this post, I use text analytics to create a better word cloud, faster.

As discussed in this post, text analytics routinely involves a pre-processing phases, where uninteresting and infrequent words are removed, spelling is corrected, words of common route are merged, phases are learned, and infrequent words are removed. This can be automated in Displayr by selecting Insert > More (Analysis) > Text Analysis > Setup Text Analysis, selecting the appropriate options in the object inspector, and then ticking Automatic.

Below, the left side shows the main output of the text analysis setup in Displayr, showing the frequency with which words appear after the text analysis. When this output is selected, as below, you can also see the settings on the right. For example, you can see the Text Variable being analyzed, which words have been removed, and that it is limited to showing words that appear 10 times or more. 

When doing this, keep in mind that pairs of words and phrases (e.g., don’t like) are better dealt with interactively in the word clouds, rather than by the text analysis.

TextAnalyticsOptions

Creating a word cloud from the tidied text

NewVariableTextAnalysis

Now that we have tidied the text data, we need to create a new variable in the data file with the tidied text. We need to do this because the word clouds take a variable as an input. To create a variable, select the output, and then select Insert > More (Analysis) > Text Analysis > Techniques > Save Tidied Text, which causes a new variable to appear at the top of the data tree, as shown to the right.

To create a word cloud, we now create a new table by dragging the new variable onto the page, and then select Charts > Word Cloud, adding any phrases that we want to appear (e.g., Tom Cruise). We then get the much tidier word cloud below.

If you want to try it yourself, click here<

data visualizationinnovationtext analytics

Comments

Comments are moderated to ensure respect towards the author and to prevent spam or self-promotion. Your comment may be edited, rejected, or approved based on these criteria. By commenting, you accept these terms and take responsibility for your contributions.

Tim Bock

Tim Bock

26 articles

author bio

Disclaimer

The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.

More from Tim Bock

Data Visualization for Conjoint Analysis
Research Methodologies

Data Visualization for Conjoint Analysis

5 min read

Visualizations can summarize patterns that are commonly hidden in a simulator

What’s Better Than Two Pie Charts?
Quantitative Research

What’s Better Than Two Pie Charts?

3 min read

Bad visuals stress the need for charts to be interpretable in seconds

Using “Small Multiples” Visualizations for Big Success
Insights Industry News

Using “Small Multiples” Visualizations for Big Success

5 min read

Visualizing data can be made easier by utilizing small charts for comparison and analysis

ARTICLES

The Human in the Room: Why Multilingual Research Needs More Than a Good Translation
Research Methodologies

The Human in the Room: Why Multilingual Research Needs More Than a Good Translation

7 min read

Discover why multilingual research requires expert bilingual moderators, translation review, and early language planning.

Jill  Bishop

Jill Bishop

Founder & CEO at Multilingual Connections

Future Trends Emerging in Mixed-Method Marketing Research
Research Methodologies

Future Trends Emerging in Mixed-Method Marketing Research

7 min read

Explore the future of mixed-method marketing research, including AI, synthetic data, continuous insights, and evolving research workflows.

Ashley Shedlock

Ashley Shedlock

Content Producer at Greenbook

When Easy Becomes Empty: The Frictionless Feedback Fallacy
Research Methodologies

When Easy Becomes Empty: The Frictionless Feedback Fallacy

6 min read

Making surveys easier doesn’t always improve insights. Discover why thoughtful feedback design balances convenience with meaningful, reflective respon...

Tarik Covington

Tarik Covington

Founder & Chief Strategist at Covariate. Human-Centered Insights

The Always-on Agency: How to Survive the Shift to Intelligence-Native Organizations
Research Methodologies

The Always-on Agency: How to Survive the Shift to Intelligence-Native Organizations

4 min read

The insight agency model is under pressure. In an always-on world, success depends on becoming a decision partner, not just a supplier of research pro...

Hannah Mann

Hannah Mann

Founding Partner at Day One Strategy

Sign Up for
Updates

Get content that matters, written by top insights industry experts, delivered right to your inbox.

67k+ subscribers