Mollom evaluates content quality and stops spam on your website by using machine learning techniques, language analysis, and a reputation system. Instead of having to spend your time moderating generated content, you can instead concentrate on building and improving your website.
How Mollom works
Mollom employs three specific technologies to detect spam and malicious content:
- Machine learning
Mollom uses sophisticated machine learning techniques to block spam and malicious content automatically. Mollom uses a reputation-based system that keeps a continually evolving archive of user profiles to immediately discern an individual’s propensity to submit spam. This applies to everything from user registration forms to blog entries.
- Protection against profanity
Using text analytics, Mollom is able to detect harmful content such as profanity and other spam-related content. And Mollom adds language support, stopping unwanted content in 75 languages.
- Centralized CAPTCHA service
Mollom provides a centralized CAPTCHA service that stops known spammers. Approved users are not required to solve a CAPTCHA.
The CAPTCHA is invoked for three specific use cases:
- Upon user registration, when no content can be classified
- When Mollom is unable to classify a user
- When a site owner using Mollom opts for more privacy, and Mollom isn’t allowed to audit all content
Mollom audits the content quality by defining it across the three dimensions of Spam, Ham, and Unsure:
- Ham is considered positive content and automatically published.
- Spam is negative content and automatically blocked.
- Unsure is anything in between. Mollom does not recognize the user, the user is provided with CAPTCHAs, and the customer gets to decide if content is automatically published, blocked, or sent for manual moderation.
Getting started with Mollom
To use Mollom with your website, complete the following steps: