AI-Powered Moderation: Social Media Management Tool Speeds Up Content Review Accuracy by 70%
About the Client
The client has a social media management tool that empowers users to manage their online footprint across various platforms like Twitter, Instagram, and Facebook. The tool uses AI to scan social media posts for unprofessional content, allowing users to curate their profiles and maintain a professional image. Additionally, the platform offers an educational course to promote responsible social media practices, fostering a safer and more professional online space.
Their Challenges
Inaccurate Flagging
The client's existing video moderation system struggled with accuracy. Playful interactions and harmless content were mistakenly flagged, requiring unnecessary manual review. Irrelevant and offensive labels added confusion and slowed down the moderation process.
Technical Expertise Bottleneck
The existing system struggled to handle the growing volume of user-generated content on the platform. This limited the tool's ability to moderate content and maintain a safe online environment effectively.
The Solution
Transfer Learning for Customization
Pre-trained models like Kinetics and Moments in Time from TensorFlow Hub were used to accelerate training and ensure accuracy. Transfer learning techniques fine-tuned these models with the client's specific data, ensuring they could identify acceptable content within their unique context.
IMPACT
Enhanced Accuracy
Custom models now identified harmful material with 70% accuracy and have reduced false negatives by 80%
IMPACT
Improved User Trust
Proactive content removal built trust and encouraged continued user engagement. Accurate moderation helped the client comply with regulations and mitigate legal issues
Multi-Functional Content Analysis
The solution categorized videos into various classes including racial bias, personal attacks, profanity, threats, and sexually explicit content. It analyzed audio data extracted from videos to further classify text content within the video. A user-friendly RESTful API enabled smooth integration with the client's existing systems.
Success Story Highlights
The client's social media management tool achieved significant success with its enhanced content safety measures. Custom models now identify harmful material with 70% accuracy and have reduced false negatives by 80%. This increased content flagging accuracy also cut-down human review time by 90%. This success extends beyond internal benefits, opening doors to a potential new revenue stream by offering their content moderation services to other businesses.
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