Analysis Result
Interpretation:
Overall Score
Sentiment
Focus
Complexity
Emphasis
Words
Lexical Diversity
Keyword Hits
Metric Graph
Detailed Metrics
| Metric | Value |
|---|
Calculator
About This Calculator
This quote analysis calculator helps evaluate short or long quotations with a structured AI and machine learning style review. Instead of stopping at word count, it measures sentiment direction, keyword focus, complexity, emphasis, and lexical variation. That combination is useful when reviewing prompts, outputs, interview excerpts, customer comments, policy statements, or research notes.
The calculator treats each quote like a small text sample. It tokenizes the passage, estimates sentence length, checks long-word ratio, compares unique words against total words, and looks for positive, negative, and certainty terms. If you add focus keywords, the tool measures how strongly the quote stays on topic. This makes the page helpful for evidence review, bias checks, tone inspection, annotation work, and lightweight language feature scoring.
Weighted scoring adds flexibility. You can raise sentiment weight when tone matters most, increase focus weight when topic alignment matters more, or give extra value to complexity when reviewing analytical writing. Emphasis scoring detects uppercase words and strong punctuation patterns, which helps flag forceful language. The result is a compact but advanced workflow for comparing quotes with one repeatable method before moving into deeper NLP pipelines or human review.
Example Data Table
| Reference | Quote Sample | Sentiment Score | Focus Score | Overall Score | Interpretation |
|---|---|---|---|---|---|
| Model Output A | This system clearly improves accuracy and supports reliable forecasts. | 72.00 | 64.00 | 68.30 | Positive and focused |
| Policy Review | The quoted statement raises bias concerns and shows limited supporting detail. | 34.00 | 58.00 | 49.80 | Cautious negative framing |
| Research Note | The passage uses technical language, dense phrasing, and strong topic alignment. | 55.00 | 70.00 | 66.10 | Technical focused quote |
| User Feedback | This answer feels weak, uncertain, and difficult to trust fully. | 28.00 | 41.00 | 38.60 | Negative low-confidence quote |
Formula Used
- Word Count = total detected tokens in the quote.
- Sentence Count = total sentence splits from punctuation markers.
- Average Sentence Length = Word Count ÷ Sentence Count.
- Average Word Length = total word characters ÷ Word Count.
- Lexical Diversity = (Unique Words ÷ Word Count) × 100.
- Long Word Ratio = (Long Words ÷ Word Count) × 100.
- Sentiment Score = clamp(50 + ((Positive Hits − Negative Hits) ÷ Word Count) × 200).
- Focus Score = clamp((Keyword Hits ÷ Word Count) × 500).
- Emphasis Score = clamp((Uppercase Ratio × 4) + (Exclamations × 12) + (Questions × 8) + (Repeated Punctuation × 15) + (Certainty Ratio × 1.5)).
- Complexity Score = average of normalized sentence length, long-word score, and lexical diversity.
- Overall Score = weighted average of Sentiment, Focus, Complexity, and Emphasis scores.
How to Use This Calculator
- Paste the quote into the main text area.
- Add a reference label if you want clearer exports.
- Enter optional focus keywords for topic alignment scoring.
- Add custom positive, negative, and certainty terms if needed.
- Set the long-word threshold to match your review style.
- Adjust the four weights to match your evaluation priority.
- Click Analyze Quote to display results above the form.
- Use the CSV or PDF buttons to export the current analysis.
FAQs
1. What does this calculator measure?
It measures sentiment, topic focus, lexical diversity, complexity, emphasis, and an overall weighted score for one quote or short passage.
2. Is this tool useful for AI output review?
Yes. It helps compare generated responses, quoted evidence, moderation text, and annotation samples with one repeatable scoring method.
3. Can I use my own keyword lists?
Yes. You can enter custom positive, negative, certainty, and focus keyword lists to adapt the scoring model to your project.
4. What does focus score mean?
Focus score estimates how strongly the quote matches your chosen topic keywords. Higher values suggest tighter topical alignment.
5. Why does a neutral quote still get a score?
Neutral language still has measurable structure, complexity, and emphasis. The overall result reflects multiple dimensions, not sentiment alone.
6. Does this replace full NLP pipelines?
No. It is a lightweight review calculator. It supports fast screening before deeper modeling, manual annotation, or full production analysis.
7. What raises the emphasis score?
Uppercase words, exclamation marks, question marks, repeated punctuation, and certainty terms raise emphasis because they signal stronger expression.
8. Can I export the results?
Yes. The calculator includes CSV and PDF download options for the current result set and summary text.