How to Manually Classify Text Data

If you don't want to use AI-assisted text classification, as described in How to Classify Text Data, you can instead manually classify your text data.

This article describes how to go from a raw text variable...

...to a state where the text verbatim responses have been manually classified into a new variable and can be used for further analysis:

This article contains the following sections:

• Start Categorization
• Create Themes
• Classify Text Responses
• Use Similarity Sorting to Assist With Classification
• Other Sorting Options
• Use Filtering to Assist With Classification
• Reusing Existing Categorization

Requirements

• A Text variable containing verbatim responses. Text variables are represented by an A next to the variable in the Data Sources tree:

Start Categorization

1. In the Data Sources tree, select the text variable that you would like to classify.
2. Hover and click + > Text Categorization.
3. Select whether a text response should be categorized into one or multiple themes:
   1. Multiple themes - use this when you have open-ended responses or miscellaneous responses
   2. Only one theme - use this for things like top of mind awareness, spontaneous awareness mentions, or where the response is just one thing
4. Click Start.

If you're not sure which option is best for the text data you're working with, see Finding the Best Text Analysis for Your Data for examples.

The text categorization window will open with the original text responses appearing on the right:

Create Themes

1. To add a new theme, you can take one of the following actions:
   • Clicking on + Add New Theme at the bottom of the Themes list, typing in a label, and hitting enter.
   • Dragging a text response to the left and into the purple box at the bottom of the Themes list.
   • Hovering over a response, clicking Manually classify, typing in a new theme label, and hitting Enter.
2. Repeat for any new theme(s) that you'd like to include.

Classify Text Responses

Next, start classifying the text responses into themes.

1. Select the text response.
2. To add it to a theme, drag and drop it into the new theme, or hover and click Manually classify, and start typing the new theme's label and select it.
3. OPTIONAL: If you selected Multiple themes when starting the categorization, you can drag and drop into an additional theme, or hover over a theme, click  Manually classify, and start typing the theme's label.
4. OPTIONAL: To remove a response from the current assigned theme and add it to another, click on the triple letters in the Classification column, remove the assigned theme by clicking on the X to the right of the label, start typing the correct theme, and hit Enter.

Below, "drink for the enjoyment and the fun it brings" is added to "Social perception" and removed from "Brand loyalty".

Once you are done classifying the text responses into themes, click Save.

A new variable will appear in the Data Sources tree with "Categorization" in the name. This variable can be used in tables and other outputs.

Use Similarity Sorting to Assist With Classification

You can use our Similarity algorithms to help you manually classify remaining text data into existing themes. This can be accessed via the Show response similarity to theme or text button:

Similarity to Text

You can enter text in the similarity filter to find responses that are similar in the unclassified data.

1. Click the Show response similarity to theme or text button .
2. Enter a keyword or phrase that you want to find similar matches for in the search field.
3. Click the Text that appears in the Similarity to text area:

The responses will update to show an orange bar to the left of the text. The length of the bar indicates the match level, so the longer the bar, the better the match.

In the example below, I have some text data that contains responses to what people miss about pre-pandemic life. I used the similarity algorithm to find responses that are similar to "travel":

To assign the results to an existing theme:

1. Select the response(s) from the pane on the right that you want to classify.
2. Either drag and drop into the appropriate theme, or hover and click Manually classify, start typing the theme's label, and then select the theme from the list.
3. OPTIONAL: You can assign to multiple themes by selecting them from the list of themes using Manually classify, or dragging the text into an additional theme.

Similarity to a Theme

You can enter text in the similarity filter to find responses that are similar to themes as well. The algorithm will look at responses that have been classified to a specific theme, and then use those to find similar responses in the unclassified data. The algorithm becomes smarter as more responses are classified to a theme.

1. Click the Show response similarity to theme or text button .
2. Enter a keyword or phrase that you want to find similar matches for in the search field.
3. Click the theme that appears in the Similarity to theme area:

The responses will update to show an orange bar to the left of the text, and include any responses that have already been classified. The length of the bar indicates the match level, so the longer the bar, the better the match.

To assign the results to an existing theme:

1. Select the response(s) from the pane on the right that you want to classify.
2. Either drag and drop into the appropriate theme, or hover and click Manually classify, start typing the theme's label, and then select the theme from the list.
3. OPTIONAL: You can assign to multiple themes by selecting them from the list of themes using Manually classify, or dragging the text into an additional theme.

Other Sorting Options

Alphabetically

Sort text responses alphabetically to find items that are similar to each other or help you determine which new themes to add. To sort alphabetically, click the arrow next to Response. The first time you click it, it will sort in ascending alphabetical order. If you click it twice, it will sort in descending order. Clicking a third time will reset things to the default sort order (i.e., by order of cases).

Number of responses

Use the Count sort option to sort the text responses. This can help you determine which themes to add as well as assign responses to themes. To sort by number of responses, click the arrow next to Count. The first time you click it, it will sort in ascending order. If you click it twice, it will sort in descending order. Clicking a third time will reset things to the default sort order (i.e., by order of cases).

Use Filtering to Assist With Classification

There are a number of ways that you can filter your responses within the text categorization interface.

Filter by Locked Responses

To view only locked or unlocked responses, click the Lock icon. By clicking the icon once, only the locked responses will appear. Clicking the lock again will filter to all unlocked responses. If you click the lock a third time, the sorting will be reset entirely.

Filter Responses by Text

You can search for specific text or text strings by clicking on the magnifying glass:

Then you can enter text to search for in the responses:

Filter by Theme

When you have a long theme list, you can search within or filter this list by clicking on the magnifying glass within the Themes section.

You can also filter the responses list by the assigned theme by clicking on the Theme filter in the Responses section:

Filter by Variable

An alternative to filtering by a text search term or theme is to filter by a variable in your document. Any variable that has Usable as a filter ticked under Data > Properties in the object inspector can be selected in the Var filter.

This option will display responses that were made by respondents who fall under the selected filter, but if categorized, all respondents with that response will be categorized, regardless of whether they fall into the filter or not.

You see if some responses come from respondents in a different filter, when you see an "of" count next to a response, such as [1 of 2]. This indicates that only 1 of the 2 respondents who gave this response fall into the filter. If you now classify these responses into a theme, it will classify all instances of this response (2) regardless of the filter. So in this case, classifying "hugging" will apply to both responses and not just the one that falls within the selected filter. 

When you are finished updating your classification and assigning responses to themes, click Save.

Reusing Existing Categorization

If you want to use existing themes from an already classified variable on an unclassified text variable and still be able to make use of features available in Displayr's categorization tool, you can reuse existing categorization.

For example, I have a text variable that asks about how social life has changed due to the pandemic that I classified. Next, I want to apply the same themes to another text variable that asked about what parts of social life from pre-pandemic are missed. I can reuse the existing categorization on this other text variable.

1. Select the text variable that you want to classify using existing themes.
2. Hover and click + > Text Categorization.
3. Click the Reuse Existing Categorization tab.
4. Select the variable that contains the existing themes that you want to use.
5. Click one of the following options:
   • Reuse by duplicating - copies an existing code frame and rules as is from a categorized variable set.
   • Reuse by sharing - shares an existing code frame and rules from a categorized variable set, so that any additions and changes will be reflected in both.
6. The text responses will appear on the right side, and the existing themes appear in the Themes pane to the left. To assign the text responses to an existing theme, click Classify.
7. Repeat the steps in Create themes and Classify text responses sections above as needed.
8. Click Save when you are finished with classification.

You can also reuse an existing categorization in a completely different document by exporting the code frame from the module and importing it into the other document. See How to Reuse an Existing Categorization (Code Frame) in a Different Document for more details.

Next

Text Analysis Video

Finding the Best Text Analysis for Your Data

How to Classify Text Data

How to Refine and Edit Text Categories After Categorization

How to Reuse an Existing Categorization (Code Frame) on a Different Variable

How to Back Code Variables in Displayr