Developing a Short Video Social Platform for a Korean Film Producer

In-Video Interaction: Implementing real-time interactions such as likes and comments directly within videos required precise synchronization and seamless user experience. The challenge was to ensure that these interactions occurred instantaneously without disrupting video playback.
High Performance and Scalability: The platform needed to load and play videos instantly while handling more than 10,000 concurrent users. Achieving this required a highly efficient backend and optimized video streaming protocols to maintain high performance under heavy load.
Content Moderation and Auto-Suggestions: The system needed to automatically filter and monitor uploaded videos for content violations, ensuring compliance with community standards. Additionally, it had to provide personalized video recommendations based on user behavior, requiring advanced machine learning algorithms.
Language Barriers: All documentation, wireframes, and designs provided by the client were in Korean, and the system needed to support multiple languages. This posed challenges in ensuring accurate translation and implementation across different languages while maintaining the integrity of the user experience.

Real-Time Interaction Implementation: We utilized WebSocket and Node.js for real-time communication, with Redis handling the high volume of interactions like likes and comments. This setup ensured instantaneous feedback within videos, with response times under 100 milliseconds, providing a seamless user experience.
Optimized Video Streaming and Scalable Infrastructure: We implemented AWS CloudFront for content delivery and HLS for adaptive streaming, supported by Docker and Kubernetes for scalable infrastructure. This combination allowed the platform to handle over 15,000 concurrent users with video loading times under 2 seconds, ensuring high performance and availability.
Advanced Content Moderation and Recommendation Engine: Using Google Cloud Vision API and TensorFlow, we automated content moderation to filter inappropriate videos, achieving a 98% accuracy rate. Apache Kafka and Apache Spark powered the recommendation engine, increasing user engagement by 30% through personalized video suggestions.
Multi-Language Support and Collaboration: The platform was built with Symfony and React.js, using i18next for multi-language support and Amazon Translate for automated translations. This ensured a smooth and culturally accurate experience across different languages, tailored to the global user base.

Real-Time Interaction Success: The implementation of real-time in-video interactions was highly successful, with response times of less than 100 milliseconds, ensuring a smooth and engaging user experience.
High Performance and Scalability: The platform was able to handle over 15,000 concurrent users during peak times, with video loading times averaging under 2 seconds. The use of a CDN and adaptive streaming resulted in a 40% reduction in buffering, significantly enhancing the user experience.
Effective Content Moderation and Personalized Recommendations: The AI-powered content moderation system successfully filtered out 98% of inappropriate content automatically, reducing the need for manual moderation. The recommendation engine led to a 30% increase in user engagement by suggesting videos tailored to individual preferences.
Seamless Multi-Language Experience: The system’s multi-language support was implemented flawlessly, allowing users from different regions to interact seamlessly. The accurate translation and integration of Korean language content ensured that the platform met the client’s expectations while appealing to a global audience.

Short video network platform