Word Frequency Counter

Count how often each word appears in a text and report totals plus the most frequent word.

Description

Count how often each word appears in a text and report totals plus the most frequent word.

Word Frequency Counter is a focused tool for the following task. Count how often each word appears in a text and report totals plus the most frequent word. It reports Total words, Unique words, Most frequent, Frequencies from the values you provide rather than inventing measurements, coefficients, or professional judgment that are not part of the input.

When to use Word Frequency Counter

Use this text operation when its stated character encoding, token boundaries, normalization, case handling, and output format match the surrounding workflow.

Text
Required string. Text to analyse.
Case sensitive
Optional boolean. Treat differently cased words as distinct.

The cited overview of Text processing supplies background for the terminology and domain context used by this tool.1

How Word Frequency Counter works

Count how often each word appears in a text and report totals plus the most frequent word. Inputs are interpreted exactly in the displayed units and the calculation returns the following fields without presentation rounding.

Total words
Returned integer. Total number of words found.
Unique words
Returned integer. Number of distinct words.
Most frequent
Returned string. Most frequent word, ties broken alphabetically.
Frequencies
Returned object. Word counts sorted alphabetically.

Limitations and assumptions

  • Unicode normalization, locale, grapheme clusters, malformed input, ambiguous syntax, and implementation-specific conventions can change text-processing results.
  • Use finite inputs in the displayed units, preserve source measurements and assumptions, and independently verify consequential decisions.

Alternative or Complementary approaches

Preserve the original text, test representative non-ASCII and malformed cases, and use a standards-aware parser or serializer when interoperability matters.

References

  1. Text processing — Wikipedia contributors

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