---
language: en
title: "Aggregated sentiment score"
description: "Aggregated sentiment score summarizes tone classifications. The scale, unit, weights, and basis must be known to compare results or time periods."
canonical: "https://tropk.ai/en/resources/glossary/aggregated-sentiment-score"
last_modified: "2026-10-12T16:12:09.687Z"
---

# Aggregated sentiment score

Reviewed on 2026-10-06.

## What it means

Aggregated sentiment score combines tone classifications into a single value for a defined set. Its interpretation depends on the scale, rubric, classified unit, and weights applied. A percentage of positive claims and an average rating are different aggregations. The metric’s name alone does not reveal the formula or allow comparisons between providers.

## Why it matters for marketing

The aggregate helps a marketing team track a summary, provided they can examine its components. Without that view, a frequent topic may hide criticism of another attribute, or a platform with more responses may dominate the calculation. The report needs to specify what was grouped to guide further investigation, especially when the value changes.

## Example in practice

In a hypothetical protocol for a gym chain, each claim about customer service has equal weight and is classified as positive, negative, or inconclusive. There are 36 positive claims, 24 negative claims, and ten inconclusive ones. The team defines the score as the proportion of positive claims among the 60 classified ones: 60%. It also reports the ten exclusions and examines the attributes, since the summary does not describe every unit in the chain.

## How to apply or verify

Check the dashboard documentation before recalculating. Record the scale, unit, weights, platforms, time window, and how neutral or ambiguous responses are handled. Profound’s Sentiment help article, consulted in October 2026, describes an average of positivity across platforms and weighting claims by frequency. That description does not justify inferring implementation details that the document does not specify.

## Important distinctions

The taxonomy uses Aggregated sentiment score; the operational help article uses Sentiment Score. The relationship between the names should be checked on the surface being analyzed, without turning a summarized description into a universal formula. Changes to the rubric or weights break historical comparability. The result remains a summary of the tone of responses, not a satisfaction survey.

## Sources and references

- [The AI Search Glossary: A definition of 300+ terms](<https://www.tryprofound.com/blog/ai-search-glossary>) — Profound
- [About Sentiment](<https://help.tryprofound.com/articles/3189907319-about-sentiment>) — Profound
- [Profound glossary](<https://help.tryprofound.com/articles/9363559589-profound-glossary>) — Profound

## Continue a leitura

- [Sentiment drift](</en/resources/glossary/sentiment-drift>)
- [Sentiment prompt](</en/resources/glossary/sentiment-prompt>)
- [Sentiment in AI](</en/resources/glossary/sentiment-in-ai>)

## About the author

[Luiz Gardelin](</en/team/luiz-gardelin>)

Luiz Gardelin is the founder of Tropk.ai and works in GEO/AEO, product vision, strategy, and growth, helping brands understand and improve their presence in AI responses.

---

[All pages in Markdown](<https://tropk.ai/sitemap.md>)