# Open Text Analysis

Open-ended responses often contain the most valuable insights but also the most complexity. Artemis uses AI-powered semantic analysis to interpret, summarize, and structure qualitative feedback at scale.

Instead of manually reading hundreds or thousands of comments, users can request structured insights directly.

Artemis can:

* Summarize recurring themes
* Detect positive, negative, and mixed sentiment
* Cluster comments by meaning
* Highlight emerging concerns
* Extract representative quotes
* Group open texts results along with other survey question answers

### 🔎 Theme Discovery & Summaries

* “Summarize the main themes from the Comment Question.”
* “What are customers talking about the most based on the Comment Question?”
* “Provide a high-level overview of recent comments based on the Comment Question.”
* “Identify the top 5 recurring feedback themes from the Comment Question.”
* "Provide the main themes of the Comment Question and group them by the Country Question"

Outputs may include structured summaries, categorized themes, and concise narrative overviews.

### 😊 Sentiment Analysis

* “Analyze sentiment in recent comments based on the Comment Question.”
* “Show positive vs negative feedback distribution based on the Comment Question.”
* “Highlight the most critical comments based on the Comment Question.”
* “Identify strongly positive testimonials based on Testimonial Question.”

Artemis provides sentiment breakdowns and contextual interpretation, not just raw tagging.

### 🧩 Comment Clustering

* “Cluster comments by topic.”
* “Group similar feedback together.”
* “Identify patterns in service-related complaints.”
* “Segment comments into key discussion categories.”

This helps transform unstructured feedback into actionable insight groups.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.ngsurvey.com/ai-suite/artemis-ai-agent/data-analysis-and-reporting/open-text-analysis.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.