AI Comment Moderator Keep your comment section free of insults

Introducing AI Moderators, an innovative new software solution that allows users to automatically clean up their comment section of insults, inappropriate language, and any other type of toxic content. AI Moderators use advanced Artificial Intelligence (AI) and JavaScript technologies to detect and moderate all comments before they are uploaded into the database, taking the hassle out of managing your comment section.

This software is easy to understand and deploy, with no prior AI experience needed. The user can quickly and easily set up a web-based environment using PHP, Javascript, HTML, and CSS for optimum performance.

The user will also receive mock article pages and a database structure to help set up the software in a few simple steps. First, the user needs to install a web server, such as Apache, Nginx, or IIS, with PHP and MySQL. The user then needs to run the SQL script into their database server, and then edit the DAL.php file with their database connection credentials. Finally, the user needs to extract the compressed file and copy the folder into the document root folder of the web server.

AI Moderators use TensorFlow JS and a pre-trained model for toxicity detection. The software also uses Bootstrap, SweetAlert, and Jquery to ensure smooth operation. The text classification corresponds to statistical probabilities, meaning that the accuracy is not 100%. The language supported is currently English and proper spelling is required.

With AI Moderators, users can rest easy knowing their comment sections are free of insults and toxic language. The software takes out the guesswork and allows for greater efficiency in moderating and managing commentary sections. AI Moderators is the perfect tool for any website or blog that needs an efficient and comprehensive way to handle their comment section.

Execution Steps:

• Install a webserver (for example: apache, nginx, IIS etc)


• Install PHP into the web server and mysql


• Run the sql script into your database server


• Edit the file DAL.php with your database connection credentials


• Extract the compressed file and copy the folder into the Document root folder of your webserver.

External sources:

The following website uses TensorFlow JS, as well as a pre-trained model for the toxicity detection. You will need the following libraries to load the Neural Networks and model: It also uses Bootstrap, sweetAlert and Jquery: (* MIT Credit to the corresponding authors) 

Limitations :
The text classifications correspond to statistical probabilities, hence the accuracy is not 100% guaranteed.

Proper spelling is required.
The supported language is English.