Collection Builder
Build and export custom emoji collections. Create themed sets for projects, presentations, or social media.
GeneratorYour collection is empty. Search above to add emojis.
Saved Collections
How to Use
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1
Search and add emoji to your set
Use the search bar or category browser to find emoji, then click the plus button to add each one to your collection. Collections can contain up to any number of emoji and can be reordered by drag-and-drop.
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2
Name and organize your collection
Give your collection a descriptive name and optionally add labels or group emoji into subcategories. Collections are stored in your browser's local storage or can be exported as a JSON file for use in other tools or code.
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3
Export in your preferred format
Export the collection as a JSON array of codepoints, a newline-separated text file, a JavaScript array, a Python list, or a copy-all string. Each export format includes the emoji characters and their Unicode codepoints for downstream processing.
About
Building and managing custom emoji collections bridges two domains: the Unicode character model, which defines the canonical identity of each emoji, and application data design, which determines how collections are stored, transmitted, and rendered. At the Unicode level, each emoji in a collection is best represented by its fully-qualified codepoint sequence as defined in emoji-test.txt โ this ensures portability across tools, languages, and platforms. Storing emoji as raw Unicode strings (rather than shortcodes or platform-specific IDs) makes collections language-agnostic and future-proof against shortcode dictionary changes.
For web applications, rendering a custom emoji collection requires choosing between three approaches: relying on OS system fonts (zero dependencies, but platform-specific glyphs), using a bundled emoji font like Noto Color Emoji (consistent rendering, but adds ~10MB to bundle size), or serving individual emoji as SVG/PNG assets from a library like Twemoji (granular control, best for performance at scale using lazy loading). Each approach has different implications for visual consistency, load performance, and maintenance overhead as new emoji versions are released.
Emoji collection use cases range from content moderation allow/block lists to custom keyboard subsets for specialized applications (children's apps, accessibility tools, domain-specific communication platforms). The Unicode emoji-data.txt file provides metadata useful for filtering collections by property โ for example, building a collection of only skin-tone-modifiable emoji (those with the Emoji_Modifier_Base property) or only fully-qualified sequences. The CLDR annotation dataset adds searchability across languages, enabling multilingual collection interfaces without maintaining separate keyword databases per locale.