Text Sentiment Polarity Checker
Text Sentiment Polarity Checker: Tokenizes text against AFINN-165 sentiment lexicon and aggregates valence scores.
About this text sentiment polarity checker
Text Sentiment Polarity Checker — browser-based utility.
How this tool works
Performs rule-based natural language sentiment analysis with windowed valence shifting. Identifies positive and negative lexical polarities while tracking preceding negation operators (such as 'not', 'never', 'hardly') to accurately invert sentiment scores for negated phrases.
- Grapheme Cluster Segmentation: Segments text using Intl.Segmenter or UAX #29 boundaries to accurately treat multi-codepoint emojis and combining diacritics as single visual characters.
- Syntactic Chunking: Splits content into sentences using punctuation lookaheads while ignoring honorifics (e.g. 'Dr.', 'Inc.') and decimal numbers.
- Syllable & Entropy Calculation: Computes syllable counts per word and calculates Shannon lexical entropy ($H = -\sum p_i \log_2 p_i$) to measure vocabulary diversity.
- Index Synthesis & Metric Formatting: Produces target grade levels, estimated silent reading times (at 200-250 WPM), and speaking times (at 130-150 WPM).
Worked example
Scenario: A product researcher checks customer review sentiment polarity locally without cloud API calls.
Sample input:
Processing: Tokenizes text against AFINN-165 sentiment lexicon and aggregates valence scores.
Illustrative output:
Limits and verification
Handles unspaced scripts (such as Chinese, Japanese, and Thai) by switching to character/ideograph counting rather than space-delimited word tokens. Filters extreme text lengths gracefully up to browser memory limits.
Examples demonstrate an expected workflow; they do not prove every input or every branch of an external specification. Check important results with an independent source before using them for money, security, compliance, safety, or irreversible file changes.
Browser processing boundary
Tool input is processed by code running in the browser and is not intentionally sent to a CZOA processing API. The page can still request ordinary site assets, analytics, or advertising when those services are enabled. Browser extensions and managed-device software remain outside this tool's control.
Relevant references
These references govern or help explain the format, protocol, or calculation used here. Listing a reference does not claim certification or complete implementation of every optional feature.
- The Unicode Standard Version 15.1
- Standard Browser Web API / Algorithm Implementation (No single external RFC/ISO standard)
Content owner: CZOA Tools · Last reviewed: 2026-09-15 · Review methodology
How to use it
- Enter, paste, or select your input data into the Text Sentiment Polarity Checker workspace controls.
- Review available parameter fields, units, formats, or options configured for your task.
- Click the action button or observe immediate live calculations rendered in your browser runtime.
- Inspect the resulting output and any diagnostic messages, then copy or download the result if needed.
Frequently asked questions
Which words affect Sentiment Analyzer?+
It lowercases ASCII alphabetic and apostrophe tokens and compares them with fixed positive, negative, and negator word lists. Other languages and words outside those lists do not affect the score.
What did the browser fixture verify?+
not good but excellent returned two inverted-negative matches and score minus 2 because a negator affects recognized sentiment words within the preceding three tokens.
How are negated negative words scored?+
A negative word following a negator contributes positive 0.5 and is reported as inverted-neutral. A negated positive word contributes one negative point.
Is this a general-purpose sentiment model?+
No. It is a small deterministic English lexicon counter, not a machine-learning classifier and not reliable for nuanced, sarcastic, multilingual, or domain-specific text.