A multilingual list of profane, offensive, and inappropriate words for content filtering and moderation.
List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words is a public repository containing curated lists of words considered profane, offensive, or inappropriate in multiple languages. It helps developers implement content filtering to prevent such words from appearing in autocomplete suggestions, search results, or user-generated content. Originally created by Shutterstock to filter their image library and keyword system, it serves as a foundational resource for moderation tasks.
Developers and organizations building applications with user-generated content, search functionality, or autocomplete features who need to filter inappropriate language. It is particularly useful for those working on platforms requiring multilingual moderation.
It offers a ready-to-use, community-vetted list that saves time compared to manually compiling offensive terms. The multilingual support and open-source nature allow for customization and expansion, making it adaptable to specific cultural or regional needs.
List of Dirty, Naughty, Obscene, and Otherwise Bad Words
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Includes lists for over 25 languages, from common ones like Spanish to niche ones like Klingon, enabling broad international coverage without manual compilation.
Open for contributions, allowing lists to expand and adapt to cultural nuances over time, especially for under-represented languages.
Available as a Node.js module (`naughty-words`), providing straightforward access to word lists in JSON format for quick implementation in JavaScript projects.
Acknowledges the subjective nature of profanity with a clear philosophy focused on preventing unwanted suggestions, offering a realistic starting point for filtering.
Lists are based on community guesses and may have gaps or inaccuracies, requiring manual validation and updates to handle evolving language or regional specifics.
Filters words literally without considering intent or usage context, which can lead to false positives (e.g., blocking innocent phrases) or missed inappropriate content.
Provides raw word lists without advanced features like regex patterns, phonetic matching, or machine learning integration, limiting effectiveness in complex moderation scenarios.