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Censor Any Text By Using These Bad Words Filter APIs

Do you need to censor any text that contains inappropriate words? Here you can find the solution below!

Building applications where users post (or interact with) content will inevitably require you to detect and filter profanity. These include, to mention a few, chat rooms for video games, comment sections, and social networking applications.

Describe Profanity.

The inappropriate, vulgar, or rude use of words and language is referred to as profanity (also known as curse words or swear words). Profanity is a useful tool for expressing or demonstrating strong feelings. Profanity might give the impression that online spaces are hostile to users, which is not desired for an app that is intended for a broad user base.

You decide which words constitute profanity. This article will show you how to filter words separately so you can decide what kind of language is acceptable on your app.

Why do we catch and remove vulgar language?
To encourage constructive communication, especially when children are involved
enhancing social interactions by fostering a conducive atmosphere for communication enhancing user communities’ security
For communication spaces to automatically block and filter harmful information
to lessen the requirement for manually moderating user activity in online communities.

green and white typewriter on black textile

Common issues encountered when identifying vulgarity
Language subversions could be used by users to bypass censors.
Users may begin to manipulate the language to get around filters by creatively misspelling words or replacing letters with numbers and Unicode symbols.
When filtering content, profanity filters may not take context into account. They also frequently provide false positives, as in the Scunthorpe issue.

The time it takes to integrate profanity filtering into applications will be reduced for developers that use APIs as opposed to writing the complete code from scratch. Businesses will be able to discover and remove inappropriate language automatically with APIs that check for profanity.

Bad Words Filter API

Bad Words Filter

The filter disregards punctuation, case, formatting, etc. to employ natural language processing to translate the input into logical terms (NLP). Word transformations, which can also show words with repeating letters, excess whitespace, and special characters, can be used to detect word obfuscation. Using this API, you can censor unwanted terms from the text in addition to discovering and extracting them from it.

The API will be given a text string or URL, and it will then output a list of all the harmful terms it has discovered. You can alternatively substitute a different character for these offensive words. An asterisk or another word of your choice may be used.

By visiting the Zyla API Hub marketplace and selecting the Bad Words Filters API utility utilizing the search API engine, you can find the best tool and filter every bad word. Of course, you can also browse all of the APIs that are readily available. Take advantage of this fantastic tool!

PurgoMalum

PurgoMalum is a straightforward, cost-free RESTful online service for filtering and deleting offensive language, obscenity, and other information. The interface of PurgoMalum supports a number of customisation parameters and can provide results in plain text, XML, and JSON.

Based on an internal profanity list (you can, at your discretion, add your own terms to the profanity list using a request parameter), PurgoMalum is meant to eliminate words from input text (see Request Parameters below). As an example, “@” will be recognized as a “a,” “$” will be recognized as a “s,” and so on. It is meant to recognize character alternates that are frequently used in place of normal alphabetic characters.

Additionally, PurgoMalum makes use of a list of “safe words,” or neutral phrases that contain words from the profanity list (like “class”). these secure words are excluded from the filter.

MicrosoftContentModerator

Moderation of text and images with computer assistance. Using classifiers driven by machine learning, tailored blacklists, and optical character recognition (OCR), you can better identify potentially hazardous or undesired images (OCR). The ability to automatically match content against your chosen lists and find potential obscenity in more than 100 languages is provided by MicrosoftContentModeration. The content moderator also searches for any possible personally identifying data (PII).

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