What Is Text AI?
Text AI is a feature that automatically analyzes open-ended response data collected from surveys using AI technology, classifying the content by topic, sentiment, and keywords to help you quickly identify overall trends and patterns.
It also supports automatic translation of responses collected in multiple languages into your desired language, allowing you to integrate and analyze data across different languages under one unified standard.
⚠️ Text AI analysis uses a GPT-based AI analysis service. In accordance with OpenAI's API usage policy, text data is stored on OpenAI's servers for up to 30 days for misuse monitoring purposes, after which it is permanently deleted.
Why Should You Use Text AI?
1️⃣ Quickly process large volumes of text responses.
Instead of reading through countless open-ended responses one by one, AI automatically classifies response content and organizes key information. This significantly reduces analysis time and enables faster insight generation and decision-making.
2️⃣ Save time and costs on translation and text analysis.
Without needing to outsource translation or analysis tasks externally, you can complete both translation and text analysis in one place within Dataspace, improving work efficiency.
3️⃣ Analyze qualitative data quantitatively.
Qualitative data such as open-ended responses can be quantified and analyzed through keyword frequency, response counts by topic, and sentiment (positive/negative) ratios. This also makes it possible to compare and interpret the data alongside other survey data in a comprehensive way.
When Do You Need Text AI?
✅ When analyzing customer feedback or satisfaction surveys
"There are too many responses to read through one by one. I want to quickly find out what complaints customers are mentioning most. 🤔"
🧙 Here's how you can use it
Topic analysis lets you automatically extract recurring issues and opinions from responses. This helps you quickly identify the problems or areas for improvement that customers frequently mention.
Sentiment analysis automatically classifies each response as positive, neutral, or negative, giving you a clear at-a-glance view of overall satisfaction trends.
✅ When you need to analyze multilingual survey data together
"Responses in Korean, English, and Japanese are mixed together, so I have to translate them every time I analyze — it's such a hassle. 🤔"
🧙 Here's how you can use it
Use the text translation feature to automatically translate responses written in multiple languages into your desired language.
Topic analysis and sentiment analysis can be used on the translated data in the same way, allowing you to integrate and analyze responses in different languages under one unified standard.
✅ When you need to organize and aggregate short open-ended responses
"There are many short responses like brand association words, and I'm unsure how to group similar words for aggregation. 🤔"
🧙 Here's how you can use it
The text grouping feature lets you automatically group responses with similar meanings or words containing typos.
Using the grouped results, you can count how many times each keyword was mentioned, enabling more systematic analysis of short open-ended responses.
Key Features of Text AI
1️⃣ Original Responses
This feature lets you check the original text of responses directly within the 'Analytics' tab without navigating to a separate screen.
Use keyword search to quickly find specific responses.
Click the icon in the upper right of a response to mark it as an important response, and view only important responses separately.
A feature to copy response content to the clipboard is also included.
2️⃣ Word Cloud – Morphological Analysis
This feature visualizes response text at the keyword level, letting you see key responses at a glance.
The word cloud is provided by default in text analysis. It separates response text into individual keywords and visualizes them with varying sizes and colors based on frequency.
Applying morphological analysis extracts only nouns, verbs, and adjectives, giving you a more refined word cloud and keyword table.
This feature is available in various locations including the Analytics tab, Report tab, and Text AI tab.
3️⃣ Topic Analysis
Topic analysis is a feature where AI analyzes response text to automatically extract common topics and opinions, then visualizes them in a bubble chart.
Without reviewing individual responses one by one, you can quickly grasp the key topics across the entire dataset.
A 'response summary' is provided for each topic, so you can easily review the vast amount of text data in a summarized form.
4️⃣ Sentiment Analysis
Sentiment analysis is a feature that classifies the emotional tendencies expressed in response text into three sentiments — positive, neutral, and negative — and visualizes them in a gauge chart.
It provides a summary of responses by sentiment, and clicking each tab lets you also view the actual response content.
By quantifying customer reactions, you can intuitively understand the overall sentiment trends toward a brand or service.
5️⃣ Text Translation
The text translation feature supports automatic translation of text data collected in multiple languages into your desired language.
It supports translation between more than 100 languages including Korean, and allows you to consolidate text data in various languages within a project into a single analysis language — making it highly efficient.
Have you got a good understanding?
Analyzing open-ended responses is an important process for uncovering the true value of your data.
If you have any questions or need assistance during the actual analysis process, please click the [Help Center icon] in the bottom right corner of your screen at any time. Our team will do its best to help you quickly and accurately.