Sentiment Analyzer
A rule-based sentiment analyzer that scans your text against small built-in lists of positive and negative words, then reports a verdict of Positive, Neutral, or Negative along with the matched counts and a balance bar. No AI model is used — it is a transparent lexicon match that runs in your browser.
Examples
I love this product, it works great and the support was excellent.
Verdict: Positive, score +3 (3 positive, 0 negative).
How it works
The tool holds two short lists of English words, one positive (“great”, “love”, “helpful”) and one negative (“terrible”, “broken”, “slow”). It counts how many words in your text appear in each list and subtracts: score = positive − negative.
| Score | Verdict |
|---|---|
| Above 0 | Positive |
| Exactly 0 | Neutral |
| Below 0 | Negative |
This is a word count, not understanding. “Not good” scores as positive, because “good” is on the list and “not” is ignored. Sarcasm is missed for the same reason, and a long text with none of the listed words comes out Neutral. Use it for a quick first look at reviews or comments, not as a final judgement.
How to use Sentiment Analyzer
Why use this tool
Frequently asked questions
No. It uses a small fixed lexicon of positive and negative words and a simple score — fully rule-based and explainable.
Lexicon matching looks only at individual words, so sarcasm, negation, and context can fool it.
Found a bug or have an idea?
ToolOrbit is actively developed — feedback directly shapes what gets built next.
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