smog-formula
v2.0.1
Published
Formula to detect the ease of reading a text according to the SMOG (Simple Measure of Gobbledygook) formula (1969)
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11,764
Readme
smog-formula
Formula to detect the grade level of text according to the SMOG (simple measure of gobbledygook) formula.
Contents
What is this?
This package exposes an algorithm to detect ease of reading of English texts.
When should I use this?
You’re probably dealing with natural language, and know you need this, if you’re here!
This algorithm is based on syllables, whereas some others are not, which means it’s tougher to get right and slower to calculate.
See syllable
for detecting syllables.
Install
This package is ESM only. In Node.js (version 14.14+, 16.0+), install with npm:
npm install smog-formula
In Deno with esm.sh
:
import {smogFormula} from 'https://esm.sh/smog-formula@2'
In browsers with esm.sh
:
<script type="module">
import {smogFormula} from 'https://esm.sh/smog-formula@2?bundle'
</script>
Use
import {smogFormula} from 'smog-formula'
// For “The Australian platypus is seemingly a hybrid of a mammal and reptilian
// creature.” (1 sentence; 4 polysillabic words).
smogFormula({sentence: 1, polysillabicWord: 4})
// => 14.554593…
API
This package exports the identifier smogFormula
.
There is no default export.
smogFormula(counts)
Given an object containing the number of sentences (sentence
) and the number
of polysillabic (three or more syllables) words (polysillabicWord
) in a
document, returns the reading ease associated with the document.
counts
Counts from input document.
counts.sentence
Number of sentences (number
, required).
counts.polysillabicWord
Number of polysillabic (three or more syllables) words (number
, required).
Returns
Reading ease associated with the document (number
).
Types
This package is fully typed with TypeScript.
It exports the additional type Counts
.
Compatibility
This package is at least compatible with all maintained versions of Node.js. As of now, that is Node.js 14.14+ and 16.0+. It also works in Deno and modern browsers.
Related
automated-readability
— uses character count instead of error-prone syllable parsercoleman-liau
— uses letter count instead of an error-prone syllable parserdale-chall-formula
— uses a dictionary, suited for higher reading levelsflesch
— uses syllable countflesch-kincaid
— likeflesch
, returns U.S. grade levelsgunning-fog
— uses syllable count, needs POS-tagging and NERspache-formula
— uses a dictionary, suited for lower reading levels
Contribute
Yes please! See How to Contribute to Open Source.
Security
This package is safe.