Remove Duplicate Words

Remove duplicate tokens from any pasted text in seconds. This operation runs across the entire input and is case‑sensitive (run lowercase first when you need case‑insensitive results).

How to use

1. Paste your text into the editor.
2. (Optional) Normalize with linked tools — e.g. lowercase, remove punctuation, or remove non‑alphanumeric characters.
3. Open Menu → Remove → Duplicated Words.
4. Review the output and copy or export.

What this tool does (and doesn’t)

• Scope: deduplication runs across the full pasted text — not limited to adjacent words or single lines.
• Matching: exact, atomic, and case‑sensitive. "Apple" ≠ "apple" unless you lowercase first.
• Token rules: punctuation, hyphens, and spaces affect matches. Normalize formatting for reliable results.
• Not a phrase merger: this tool treats tokens literally — multiword phrases can be split unless preserved per line.

Common use cases

• E‑commerce inventory lists (EANs / UPCs / SKUs)
  Remove repeated product identifiers to avoid double imports, duplicate stock entries, and incorrect reconciliation. Recommended: run remove spaces and remove diacritics first, then dedupe.
• Tag clouds & word‑frequency visualizations
  Remove repeated tokens to get accurate frequency counts and clearer visuals. Recommended chain: lowercase → remove punctuation → remove duplicate words → extract unique words.
• Email or contact lists (pre‑import)
  Collapse duplicate addresses to prevent multiple sends and distorted metrics. Emails should usually be canonicalized first (lowercase + trim). Use case converter and trim before deduping.
• Keyword lists for SEO / PPC — topic cluster discovery
  Clean large keyword pools to reveal unique keywords and help build topic clusters. Warning: because this operation is atomic, it can break multiword phrases if phrases are not preserved. For topic clustering, keep each phrase on its own line or convert comma lists into one phrase per line before deduping. Useful chain: format lists → lowercase → remove duplicate words → extract unique words.

Examples (before → after)

Input (EANs):

4006381333931
4006381333931
9780306406157

Output:

4006381333931
9780306406157

Input (emails; case sensitive):

User@Example.com
user@example.com

Output (case sensitive):

User@Example.com
user@example.com

(► lowercase first with Case Converter to treat as duplicates)

Input (keyword CSV):

red shoes, shoes running, red shoes

Output / note:

If phrases are comma-separated and tokens are deduped atomically, multiword phrases can be split. Recommended: put one phrase per line, then dedupe.

Tool‑chaining & recommended workflows

• Canonicalize product IDs: Remove spaces → Remove diacritics → Remove duplicate words.
• Case‑insensitive keyword cleanup: Lowercase → Convert formats → Remove duplicate words → Extract unique words.
• Preserve multiword phrases for topic clusters: convert your keyword list so each phrase is on its own line, then run remove duplicated lines (if duplicates are whole lines) or use this tool carefully if you want atomic token cleanup.
• CSV import prep: extract the column → Trim → Remove spaces → Dedupe.

Tips & edge cases

• This is an atomic, case‑sensitive operation. Run lowercase first for case‑insensitive dedupe.
• Punctuation, hyphens, and different separators change matches. Normalize with Remove Punctuation or Remove Spaces when needed.
• For structured identifiers (EAN/ISBN), strip formatting characters (hyphens/spaces) before deduping to avoid false negatives.
• When working with multiword keywords you want to keep intact, place each phrase on its own line, or use line‑dedupe via remove duplicated lines.
• Always proofread results — automated dedupe can remove repeated tokens in prose that you may intentionally keep.

Note: if you need HTML or line cleanup, the original page also referenced these helpers: line breaks, remove any HTML tags, and remove duplicated lines (kept here for compatibility).

Related tools

• Remove duplicated lines
• Extract unique words
• Case Converter
• Remove Line Breaks
• Remove Spaces
• Remove Diacritics

Try the tool now — remember: case‑sensitive and across the whole text. Normalize first when you need case‑insensitive or format‑aware results.