Remove repeated words from any text while keeping each word's first occurrence, with a case-sensitive/insensitive option and a live count of removed and unique words.
A duplicate word remover scans through a body of text and strips out repeated words, keeping only each word's first appearance — the same basic idea as deduplicating a list, applied at the level of individual words rather than whole lines or list items. It's a narrow, purpose-built tool: rather than trying to understand grammar or meaning, it simply tracks which words it has already seen and discards any later repeat, which makes it fast, predictable, and easy to reason about, but also means it's best suited to content where word-level repetition is genuinely unwanted rather than grammatically necessary.
This distinction matters because ordinary English prose relies heavily on repeated words — articles, prepositions, and pronouns like 'the,' 'a,' and 'it' appear dozens of times in any normal paragraph, and removing all but the first occurrence of each would leave the text broken and unreadable. This tool is built for the cases where that isn't a concern: tag lists, keyword collections, deduplicated name or ID lists, and similar structured, word-per-slot content where each entry is genuinely meant to be unique.
When deciding which copy of a duplicate to keep, keeping the first occurrence — rather than the last, or some other rule — is the behavior that best matches how people actually build lists that end up with duplicates. Tags and keywords are usually entered roughly in order of importance or relevance, so the first mention is more likely to be the intentional, well-placed one, while later repeats tend to be accidental (pasted in from a second source, or re-typed without checking what's already there).
This also produces a stable, deterministic result: running the same input through the tool always produces the same output, since the rule ('first occurrence wins') doesn't depend on any subjective judgment about which instance is 'more important.' That predictability matters for a text-processing tool — users need to be able to trust exactly what transformation is being applied, without surprises.
Whether 'Tag' and 'tag' should count as the same word or different words depends entirely on context, which is why this is a toggle rather than a fixed behavior. For most everyday cleanup — deduplicating a casually typed keyword list, or fixing an accidentally repeated word in a sentence — case-insensitive matching is what people expect, since the capitalization difference is usually incidental rather than meaningful (someone typing 'Marketing' at the start of a list and 'marketing' later almost certainly meant the same word both times).
Case-sensitive matching becomes useful in more specific situations: distinguishing a proper noun from a common noun that happens to share spelling (like 'Apple' the company versus 'apple' the fruit), preserving intentional stylistic capitalization, or working with case-sensitive identifiers like variable names or codes where capitalization genuinely changes meaning. Having both modes available means the tool can handle either situation correctly rather than forcing one behavior on every use case.
This tool sits alongside a related but distinct tool — a duplicate line remover — and the two solve different problems. Line-level deduplication removes entire repeated lines (useful for cleaning a list where each full line is one list item, like a list of URLs or email addresses), while word-level deduplication reaches inside each line and removes repeated individual words, regardless of what else is on that line.
Choosing the right one matters: running line-level deduplication on a comma-separated tag list on a single line won't do anything useful, since the whole line is likely unique even if individual words repeat within it — that's exactly the case this word-level tool is built for. Conversely, running word-level deduplication on a list of full sentences or paragraphs will likely produce broken, ungrammatical text, since it has no awareness that some repetition is structurally necessary — that's a job better suited to line-level deduplication instead.
For text spanning multiple lines — a multi-line tag block, a list broken across several rows, or a block of pasted content — this tool tracks every word it has seen in a single running set across the entire input, not a fresh set per line. That means a word appearing on the very first line permanently 'claims' that word for the rest of the document, and any later occurrence on any subsequent line, no matter how far down, gets removed. This whole-document scope is what makes the tool genuinely useful for cleaning up scattered repetition — duplicates that crept in from merging several separate lists together, for instance, are just as reliably caught as duplicates sitting right next to each other on the same line.
Line breaks themselves are preserved throughout this process specifically so the output still visually resembles your input's structure, even though words have been removed from within it — this makes it much easier to spot, at a glance, roughly where content was trimmed, compared to an output that collapses everything into one dense, restructured blob.
Duplicate Word Remover cleans up repeated words in tag lists, keyword collections, and similar text. These related tools handle other kinds of deduplication and cleanup.