What is the difference between the two scope options?

Within each line removes duplicates independently inside every line and preserves your line structure, so a word appearing in two different lines survives in both. Across all text treats the entire input as one pool and removes repeats everywhere, joining the result with your chosen delimiter and flattening the text into a single block.

How does the Output delimiter option work?

It controls how surviving words are joined in the result: Space re-joins them with single spaces, Comma with comma-space pairs like apple, banana, and Newline puts every word on its own line. With Newline the tool doubles as a quick way to convert a paragraph into a word list, one word per row.

What does the Case-sensitive switch change?

With the switch off, comparison is case-insensitive, so Apple, apple, and APPLE are the same word and only the first variant survives. With it on, each casing is treated as a distinct word and all three survive. The switch is off by default, which matches the typical expectation when cleaning keyword lists.

Are punctuation and numbers treated as words?

Words are split on whitespace, so punctuation attached to a word stays attached — "apple," and "apple" are different tokens and both survive. Numbers count as words, and are deduplicated like any other token. If trailing punctuation causes unexpected duplicates, strip it before pasting or rely on the comma delimiter to cleanly separate values.

Can I download the cleaned output?

Yes. The Unique words result box provides a built-in download action that saves the deduplicated text as a file named unique-words.txt, so you can hand the cleaned list straight to a spreadsheet, a script, or a colleague without any clipboard copying in between.

Text

Remove Duplicate Words

Remove duplicate words from text while preserving order.

duplicatewordsuniquededupetext

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About the Remove Duplicate Words

Repeated words are everywhere in messy data: merged keyword exports, concatenated tag lists, auto-generated descriptions, and text assembled from multiple sources. They inflate word counts, pollute analytics, and look unprofessional the moment a human reads them. The Remove Duplicate Words tool strips repeats while preserving the order of first appearance — a crucial difference from alphabetizing, which would scramble your content. Paste your text and the cleanup runs live. A Case-sensitive switch controls whether Apple and apple are treated as distinct (off by default, so they count as the same word). The Scope setting chooses between Within each line — duplicates are removed independently per line, keeping your line structure intact — and Across all text, which de-duplicates the entire input as one pool. An Output delimiter dropdown lets you rejoin the cleaned words with spaces, commas, or newlines, which makes the tool double as a list-to-comma-separated converter. Live Original / Unique / Removed counters show exactly how many words disappeared, and the result is downloadable as a text file.

Hand-written guide

Examples

Input

apple banana apple cherry
Banana Cherry Date

Output

apple banana cherry
Banana Cherry Date

Note: Defaults: Within each line, space delimiter, case-insensitive. 7 words in, 6 unique.

Input

apple banana apple cherry banana

Output

apple, banana, cherry

Note: Across all text with the Comma delimiter re-joins the three unique words.

Input

Apple apple APPLE

Output

Apple apple APPLE

Note: With Case-sensitive on, each casing is a distinct word and all three survive.

How to use

1
Paste your text into the Text area; duplicates are removed live as you type.
2
Toggle Case-sensitive to decide whether Apple and apple count as the same word.
3
Set Scope to Within each line or Across all text.
4
Choose Space, Comma, or Newline from the Output delimiter dropdown.
5
Check the Original / Unique / Removed counters and download the Unique words result.

Common use cases

Deduplicating keyword lists from merged exports.
Cleaning auto-generated product descriptions with repeated words.
Building unique tag sets from multiple pasted lists.
Converting space-separated lists into comma-separated values.
Flattening word clouds into unique word lists for analysis.
Preparing vocabulary lists where order and uniqueness matter.

Best practices

Keep the default case-insensitive mode for keyword lists, where casing differences are usually accidental.
Choose Within each line when line structure carries meaning, like CSV rows or config entries.
Switch to Across all text when you want a single global set of unique words.
Pick the delimiter that matches your downstream consumer: comma for SQL IN lists, newline for one-word-per-row.
Strip punctuation before pasting if it causes near-duplicate tokens to survive.

Tips

Use the Comma delimiter to convert a whitespace list into a comma-separated string in the same click.
Choose Across all text when building a unique keyword set from multi-line exports.
Leave Case-sensitive off unless casing itself carries meaning, such as acronyms versus common words.
The Original / Unique / Removed counters update live, so keep the tool open while pasting several lists in a row.

Frequently asked questions

Yes. For every word position, the tool keeps the first occurrence and skips later repeats, so surviving words remain in the exact order they first appeared. This makes it ideal for keyword lists and text where order carries meaning — unlike alphabetical sorting, deduplication should never rearrange your content.

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