Benchmarking Multi-Modal Graph-based Social Media Popularity Prediction
Learn to predict social media popularity using multi-modal graph-based models, which can improve advertising optimization and content planning by considering both content and temporal social interaction signals
- Build a multi-modal graph-based model using historical social media data
- Run experiments to evaluate the performance of different models
- Configure the model to incorporate both content and temporal social interaction signals
- Test the model on a hold-out dataset to assess its accuracy
- Apply the model to real-world social media data to predict future popularity
Data scientists and social media analysts on a team can benefit from this knowledge to develop more accurate prediction models, which can inform strategic decisions for users, creators, and platforms
💡 Jointly considering multimodal content and temporal social interaction signals can improve the accuracy of social media popularity prediction models
📈 Predict social media popularity with multi-modal graph-based models! 📊
Key Takeaways
Learn to predict social media popularity using multi-modal graph-based models, which can improve advertising optimization and content planning by considering both content and temporal social interaction signals
DeepCamp AI