Content moderation on social media using Machine Learning

Redact and moderate foul and inappropriate language and content in social platforms.


Problem statement

Forum discussions are a popular method for obtaining consumer feedback for any business. It gives the company the customer perspective of their products and their services. Such feedback provides an opportunity and input for the business to improve and grow its base. The client had an eCommerce platform, selling a wide range of FMCG consumer items. Their platform enabled their customers to conduct discussions about the products listed on their platform. There was a need to moderate these discussion forums to maintain the tone and nature of the language used. The team performing this manual content moderation is overwhelmed and stretched with the volume of the discussion. These repetitive tasks can be automated to simplify the work and improve its quality. Our client wanted us to build an automatic content moderation system to maintain the language etiquette on their e-commerce platform. To achieve this, we were required to study and detect the nature of the language used via text recognition and redact unhealthy language for achieving moderation.

Our solution

The problem involved identifying foul language from the discussion boards and redacting them automatically. We developed a Natural Language Processing model to identify text sections that constitute unhealthy language. We then redacted the content from their discussion board using simple text management tools.

Technology stack

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