LLM Pulse analyzes sentiment at the response level first, then aggregates it to give you meaningful insights across your entire project.
Step 1: Response-level analysis #
Each time an AI model responds to one of your tracked prompts, we analyze how your brand (and competitors) are mentioned. Our sentiment analyzer classifies each mention into one of five categories:
| Category | Score |
|---|---|
| Very Positive | +1.0 |
| Positive | +0.5 |
| Neutral | 0 |
| Negative | -0.5 |
| Very Negative | -1.0 |
This analysis is performed by an AI model that evaluates the context, tone, and language used when discussing your brand or competitor.
Step 2: Aggregated metrics #
Once we have sentiment data for individual responses, we aggregate it to show you the bigger picture:
Share of Sentiment #
A breakdown showing what percentage of all mentions fall into each sentiment category (displayed as a pie/donut chart and over-time area chart).
Net Sentiment Score #
A single number that tells you the overall sentiment health of your brand.
Formula:
Net Sentiment = ((Positive + Very Positive) − (Negative + Very Negative)) / Total Mentions × 100
Score Range: -100% to +100%
- +100% = All mentions are positive or very positive
- 0% = Balanced sentiment (equal positive and negative)
- -100% = All mentions are negative or very negative
Example calculation #
Let’s say your brand received 100 mentions this month:
- Very Positive: 20
- Positive: 35
- Neutral: 25
- Negative: 15
- Very Negative: 5
Net Sentiment Score:
= ((35 + 20) − (15 + 5)) / 100 × 100
= (55 − 20) / 100 × 100
= 35%
Your Net Sentiment Score would be +35%, indicating a healthy positive sentiment overall.
How we use it #
- Sentiment Over Time: Track how sentiment evolves day-by-day, week-by-week, or month-by-month
- Competitor Comparison: See how your Net Sentiment Score ranks against competitors in the same AI conversations
- Filter by Model/Tag/Topic: Drill down to understand sentiment for specific AI models, prompt collections, or discussion topics
Key takeaways #
- Response-level first: Every individual AI response is analyzed for sentiment
- Then aggregated: Individual scores roll up into your dashboard metrics
- Net Sentiment: A quick health check ranging from -100% (all negative) to +100% (all positive)
- Actionable: Use filters to identify which topics or AI models show the most (or least) favorable sentiment toward your brand
