In this tutorial, we show how to check and make changes to variations on CleanSpeak's blacklist filter.
Variations should be:
Filtering forum posts is unique from filtering real-time chat and other user-generated content since forums are focused on specific topics. Implementing a profanity filter not only keeps the content free of profanities, hate speech, and the like; it can also help ensure that conversations stay on topic. This post covers how to best utilize a profanity filter to aid your moderation processes, limit user frustration, and keep content productive and appropriate within forums.
Chat filters come in all shapes and sizes. Whether it's hosted in the cloud or deployed on-premise right next to the application, every online community, chat room, virtual world or forum will look for a chat filtering and or moderation tool set.
Accommodating online user generated content is no longer a choice, it's necessary for any product or brand to stand out from the masses. By creating a space for users, consumers and advocates to share with one another it creates one of the most powerful of marketing strategies: social interaction.
You can’t trust an artificial intelligence system to consistently protect your online community from inappropriate content. All artificial intelligence systems suffer from two critical flaws:
Every such system on the market today suffers from these flaws. In this 2-minute video, Inversoft CEO, Brian Pontarelli, explains why CleanSpeak is a different and more effective technology.
The sixth in a series of posts about the finer points of profanity filtering...
Embedded words occur when a dictionary word or proper name contain profanity:
CleanSpeak's sophisticated profanity filter looks for dictionary words that contain profanity and safely ignores them during the filtering process. Poorly written filters will often get caught up on these simple cases and flag large number of dictionary words as profanity. CleanSpeak pulls from a large set of dictionary words and proper names in real time, over 140,000 in all, to correctly handle this situation and avoid a potentially large number of false positives without hindering performance.