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Text Analysis

Text Analysis

Owned by Carlos Carasco
Last updated: Jan 21, 2025
4 min read

The Text Analysis module is comprised of three distinct components: the Responses per Topic component, the Sentiment Trend by Responses component, and a third component with three features: Summarisation by Eureka AI, Topic & Responses Tables, and Individual Topic Visualisation.

Responses per topic

The first component starting from the left is the Responses per topic component. This component consists in two different views of the responses of topics.

In the first tab we see a breakdown by the 10 topics with more volume considering the global Filters and the timeline dropdown (1)

How it works

Responses_per_topic.jpg
Tab 1

  1. Dropdown timeline to decide the time period to select the 10 topics to display.

  2. This graph consists of a pie chart breakdown of the 10 topics

  3. Legends of the graph

In the second tab we will see the same information but in an overtime graph

  1. Dropdown timeline to decide the time period of the x-axis and to select the 10 topics to display.

  2. This graph consists of a overtime chart of the 10 topics

  3. Legends of the graph

Sentiment trend by responses

The second component from the left is the Sentiment Trend by Responses. This component features an overtime graph displaying the sentiment trend (positive, negative, and neutral) along with its volume.

How does it work

  1. Dropdown timeline to decide the time period of the x-axis.

  2. This graph consists of a overtime chart of the sentiment trend.

  3. % of the total (based in global filter and dropdown timeline) of each sentiment score.

  4. The topics with more volume related to the sentiment.

Tables & Summarisation

The next component we will discuss consists of three parts: an Eureka AI summary with insights of the text answers in your team, that also suggests five topics, a Topic Table offering valuable insights for each topic, and a Responses Table where you will be able to see each text answer and assign manually topics to each.

Eureka AI Summary

This component is the (1) of the previous image, after selecting the “Generate” button we will have the following.

  1. Sentiment score of the text answers used to create the summary

  2. Regenerate button to create a new summary

  3. Eureka AI generated text

  4. Suggested topics

Topics table

A table with a view of all the topics of the team.

  1. Topics column → with the sentiment score badge

  2. Sub topics column → with the sentiment score badge

  3. The search bar to search for topics and sub topics

  4. Responses column

  5. Individual Visualisation View → we will see this after

  6. 3 dots

    1. Edit topic

    2. Delete topic

  7. Amount of topics

  8. Pagination

Individual Topic Visualisation

In this section, you will be able to explore various insights for each topic.

It consists of five different insights.

  1. Breakdown of the topic by sentiment → % of responses that are positive/neutral/negative

  2. Eureka AI Summary based on the topic

  3. List of responses

  4. Linked topics visualisation

  5. List of sub topics

     

Responses Table

A table with a view of all the text answers of the team.

  1. Text Answer list with the question and the survey

  2. Sentiment score column of the text answers

  3. Topics attached to the text answer

  4. Add topic option to attach a topic manually to a text answer

  5. Date of the text answer column

  6. Link to open individual feedback of the text answer

Create a Topic

The create a topic flow consists in 3 steps:

  1. The name of the topic → It’s important because this will be used for the attaching text answers to the topic by the AI

  2. Parent topic selection in case you want to create a sub topic

  3. Keywords → To expand to the name of the topic, other words you want to be related to a topic when present in a text answer