# Sentiment Score

A Sentiment Score is a quantitative metric, often derived from AI-powered text analysis, that represents the emotional tone of a piece of text, such as a product review, social media post, or customer support ticket. It is the output of sentiment analysis algorithms that classify text as positive, negative, or neutral. Scores can be represented in different ways: a simple polarity (e.g., +1 for positive, -1 for negative, 0 for neutral), a scale (e.g., from -100 to +100), or a probability distribution (e.g., 85% positive, 10% neutral, 5% negative). Aggregating sentiment scores across thousands of data points provides a objective measure of public perception. A brand can track its overall sentiment score over time to gauge the impact of a new campaign or product launch. A product manager can monitor the sentiment score of reviews for a specific product to quickly identify emerging issues. The sentiment score transforms subjective qualitative feedback into trackable, comparable data, enabling businesses to monitor brand health at scale and respond proactively to changes in customer opinion.

## Additional resources: 

[Read More on Sentiment Score](https://www.alpha-sense.com/blog/engineering/sentiment-score/)
[Sentiment Analysis Strategies](https://www.42signals.com/blog/sentiment-analysis-for-strategy/)
[Consumer Sentiment Analysis by 42Signals](https://www.42signals.com/consumer-sentiment-analysis/)