Extract hashtags from text into a unique list. Review tags used in draft posts without collecting ordinary words or punctuation.
How to use
Paste the post or several captions. Copy the returned hashtags, keeping their original spelling. Letters, digits, and underscores are supported.
Example
#Writing #текст #Writing returns #Writing and #текст. #writing remains distinct from #Writing.
FAQ
Does it measure tag popularity?
No. It extracts existing tags only and does not fetch usage counts or suggest trending topics.
Related tools
A practical task
For a post audit, keep the original caption alongside its tags. The same tag can be used in different contexts, and extraction alone does not tell you its purpose. Review spelling and capitalization before combining tags from several posts.
Another useful question
Are case variants duplicates?
Exact strings are deduplicated, so differently cased versions can stay separate. Normalize case afterward only when that matches your reporting rules.
Details for interpreting the result
| Detail | Explanation |
|---|---|
| Extracted values | Extraction identifies text that matches a rule. It does not establish that the result is a real person, a working address, or a valid business value. Validate the extracted data according to its intended use. |
| Pattern and literal search | A literal search matches the typed characters. A regular expression describes a pattern with operators. Characters such as dots and brackets have different roles in the two systems, so choose the right search mode. |
| Case sensitivity | Case sensitive matching distinguishes capital and lowercase letters. Ignoring case merges some of those distinctions, but it does not turn different spellings or word forms into the same term. |
| Literal separators | A literal separator is an exact sequence of characters, including any spaces. A comma and a comma followed by a space are different separators. Match the source consistently before extracting or exchanging fields. |
| Similar looking text | Two strings can look identical but use different Unicode sequences. An accented letter can be stored directly or as a letter plus an accent. Visual similarity alone does not establish byte equality. |
| Column headers | Headers provide names for columns; they are not extra data values. Keep their order aligned with each row. When building objects, duplicate header names create ambiguity about which value belongs to a key. |
| Strings and values | The JSON string "12" differs from the number 12, and "false" differs from false. Type changes affect comparisons and imports. Keep identifiers as strings when their leading zeros or exact digits matter. |