📊 Word Frequency Counter

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Word frequencies will be calculated and displayed with statistics
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Word Count:
Original: {{ statistics.totalOriginalWords }}
Processed: {{ statistics.totalWordsProcessed }}
Unique: {{ statistics.uniqueWords }}
Frequency:
Most: {{ statistics.mostFrequent }}
Least: {{ statistics.leastFrequent }}
Average: {{ statistics.averageFrequency }}
Lexical Diversity:
{{ (statistics.lexicalDiversity * 100).toFixed(2) }}% ({{ statistics.lexicalDiversity }})
Higher values indicate more diverse vocabulary
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{{ results.length }} words shown
# Word Count %
{{ result.rank }} {{ result.word }} {{ result.frequency }} {{ result.percentage }}%
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Sample word frequencies:
1. the15 times (8.2%)
2. and12 times (6.6%)
3. quick8 times (4.4%)
4. fox6 times (3.3%)
Features available:
• Real-time analysis as you type
• Ignore common stop words option
• Case sensitivity control
• Minimum word length filtering
• Export results to CSV format
⚠️ {{ error }}
🔄 Analyzing word frequencies...

ℹ️ About Word Frequency Counter

Word Frequency Counter builds a frequency distribution from pasted text so you can see which words appear most often, how many unique words remain after filtering, and how concentrated the vocabulary is. It is useful for keyword research, content audits, transcript review, support-log triage, classroom linguistics, and quick corpus checks before deeper natural-language processing.

The counter treats runs of Unicode letters and numbers as words, converts punctuation to separators, and can optionally fold case so Risk, risk, and RISK are counted together. For example, Risk risk control audit. becomes risk: 2, control: 1, and audit: 1 with case-insensitive sorting by frequency.

  • SEO and editorial review: find repeated keywords, overused terms, and missing vocabulary in article drafts.
  • Research and surveys: summarize recurring words in interviews, open-ended responses, or notes.
  • Security and operations: count recurring hostnames, tags, product names, or incident terms in pasted reports.
  • Writing cleanup: compare top words before and after removing common words, short tokens, or case differences.

Analysis options:

  • Case sensitive: keep Word and word separate when capitalization matters.
  • Ignore common words: remove a fixed English stop-word list such as the, and, and of.
  • Minimum word length: hide short tokens so IDs, one-letter variables, or filler words do not dominate the table.
  • Sort order and result limit: rank by frequency for keyword analysis or alphabetically for glossary-style review.

Technical notes: Unicode text handling is subtle. The Unicode Text Segmentation report defines word-boundary concepts, while Unicode Normalization Forms explain why visually similar text can be encoded in different ways. JavaScript case conversion follows the ECMAScript String.prototype.toLowerCase behavior, so locale-specific casing such as Turkish dotted and dotless I may not match a language-specific tokenizer.

Limitations: this is a fast frequency counter, not a full linguistic parser. Hyphenated words, contractions, emoji, and punctuation-heavy identifiers may split differently than a search engine, database, or language-specific NLP pipeline. The common-word filter is English-focused, and the exported CSV reflects the current on-screen options rather than a persistent server-side corpus.

API Usage Example:

POST /api/tools/text/word-frequency
Content-Type: application/json

{
    "text": "The quick brown fox jumps over the lazy dog. The dog was very lazy and the fox was very quick.",
    "caseSensitive": false,
    "ignoreCommonWords": true,
    "minWordLength": 3,
    "sortOrder": "frequency",
    "maxResults": 50
}
Ready