Mollom is an intelligent content moderation web service. By monitoring content activity on all sites in the Mollom network, Mollom is in a unique position to determine if a post is potentially spam; not only based on the posted content, but also on the past activity and reputation of the poster. In short, Mollom handles incoming posts intelligently, in much the same way a human moderator decides what posts are acceptable. Therefore, Mollom enables you to allow anonymous users to post comments and other content on your site.
How it works
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 stop 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 three dimensions:
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, and they’re shown CAPTCHA’s, and the customer gets to decide if content is automatically published, blocked, or sent for manual moderation.
Mollom is currently used by more than 60,000 sites, including Sony, Adobe, LinuxJournal, Warner Bros Records, NBC, and others. Mollom has an average efficiency rate of 99.98% - which means that only 2 in 10,000 spam messages are not routinely caught by Mollom's filters. Since Mollom began operating, it has prevented over 8 billion spam posts from littering the web. Get the latest statistics at the Mollom scorecard.
- Contact Mollom Support for issues pertaining to the Mollom service.
- e.g., inappropriately blocked posts, too much spam posts getting through, etc.
- Ensure to include the Mollom session/content IDs of affected posts (which can be found in your site's Recent log messages).
- Use the issue queue for bug reports and feature requests pertaining to the Drupal module.
- Maintenance status: Actively maintained
- Development status: Under active development
- Module categories: Community, Content, Spam Prevention
- Reported installs: 56,232 sites currently report using this module. View usage statistics.
- Downloads: 643,257
- Automated tests: Enabled
- Last modified: December 11, 2015