Free Net Sentiment Score Calculator
Click the comments to build a sample and watch your Net Sentiment Score appear — NSS = % positive − % negative, with neutrals counting towards the total but not the score.
Ready to score sentiment on your own feedback?
Clicking sample comments is the easy part. On real feedback, somebody has to read every open-ended answer and decide what it means — which is why most sentiment programmes stall. Athena, our AI agent, tags open text as positive, negative or neutral as responses arrive, groups it into recurring themes and keeps your Net Sentiment Score live in feedback analytics. Pair it with NPS, CSAT or CES to see the score and the reason behind it in one place.
Frequently Asked Questions
What is Net Sentiment Score?
Net Sentiment Score (NSS) is a single figure that summarises how a body of text leans overall. Each mention — a review, a comment, a survey answer, a support message — is classified as positive, negative or neutral, and the score is the percentage of positive mentions minus the percentage of negative ones. It runs from -100 to +100.
How do you calculate Net Sentiment Score?
Classify every mention as positive, negative or neutral, then subtract the share of negative mentions from the share of positive ones. The formula is NSS = % positive - % negative. If you analyse 1,000 comments and find 600 positive (60%), 200 negative (20%) and 200 neutral (20%), your Net Sentiment Score is 60 - 20 = 40.
Do neutral mentions count in the calculation?
Both conventions exist. Most teams include neutral mentions in the total, so they dilute the score without pushing it in either direction — that is the default in this calculator. Others compute the score over polarised mentions only, which produces a larger number from the same opinions. Either is defensible; what matters is picking one and never changing it mid-series, because the switch alone can move your score by tens of points.
What is the difference between a sentiment score and a Net Sentiment Score?
A sentiment score is assigned to a single piece of text and usually runs from -1 to +1. The Net Sentiment Score aggregates those individual labels across a whole set of texts into one figure. The sentiment score is the input; the Net Sentiment Score is the output. You cannot have the second without the first.
What is a good Net Sentiment Score?
Above 0 means more positive than negative mentions, which is the floor rather than the goal. Between 20 and 50 is good, and above 50 is excellent. Below 0 means negative feedback dominates. Treat these as rough bands, not benchmarks: NSS is not comparable across sources, because reviews skew polarised, support tickets skew negative and post-purchase surveys skew positive.
How is Net Sentiment Score different from NPS?
NPS comes from a structured question on a 0-10 scale and measures how likely someone is to recommend you. NSS is derived from unstructured text you already have, without asking anything. The arithmetic is deliberately similar — both subtract a negative share from a positive one — but NPS tells you how loyal customers are, while NSS tells you what they are talking about and how they feel about it.
Where does the text for Net Sentiment Score come from?
Any source you already collect: open-ended survey answers, support tickets and chat logs, product reviews, app store ratings, social media mentions, or email replies. The one requirement is enough volume that a few strongly worded comments cannot swing the whole score.
Are the example comments in this calculator real customer data?
No. They are illustrative examples written to show how a classifier labels short comments and how those labels roll up into a score. The sentiment values attached to them are the kind a lexicon-based model returns, not measurements from Responsly customers.
