New MMG-Pop benchmark predicts social media popularity with multi-modal graphs
Researchers combine text, images, and social interactions to forecast viral content
Deep Dive
A new benchmark called MMG-Pop and its companion model MMG-PopNet jointly model textual, visual, temporal, and social interaction signals for social media popularity prediction. Tested on four datasets from Bluesky and Reddit, the model shows superior performance and reveals insights into cross-platform training generalization and limitations of LLMs.
Key Points
- Unifies four datasets from Bluesky and Reddit under a standardized evaluation protocol
- MMG-PopNet jointly models multi-modal signals and graph-structured social interactions
- Demonstrated superior performance and insights into cross-platform generalization and LLM prediction limitations
Why It Matters
Helps platforms and creators optimize content strategy by accurately forecasting viral reach using multi-modal data.