A unified framework for cross-platform dynamic social network analysis and knowledge integration
Subrata Paul, Chandan Koner, Raj Kumar Samanta, Anirban Mitra
Problems Identified (5)
Cross-platform activity dispersion: User activity is dispersed across multiple platforms, making cross-platform dynamic social network analysis important for knowledge extraction and decision-making.
Multi-platform inconsistency: Cross-platform social media analysis must address semantic, temporal, and structural inconsistencies across platforms.
Unified social knowledge integration: The research problem is to achieve unified knowledge integration from diverse social media sources.
Cross-platform activity dispersion: User activity is dispersed across multiple platforms, making cross-platform dynamic social network analysis important for knowledge extraction and decision-making.
Multi-platform inconsistency: Cross-platform social media analysis must address semantic, temporal, and structural inconsistencies across platforms.
Proposed Solutions (5)
Unified cross-platform network framework: The paper proposes a framework for cross-platform dynamic social network analysis and unified knowledge integration.
Temporal knowledge graph integration: The methodology integrates multi-platform entities and interactions into a single temporal knowledge graph.
Identity-aligned dynamic graph construction: The methodology uses cross-platform knowledge graph construction, dynamic graph generation, and identity alignment.
Multi-analysis social network modules: The approach enables modular community discovery, subject modelling, and diffusion analysis over the integrated graph.
Unified cross-platform network framework: The paper proposes a framework for cross-platform dynamic social network analysis and unified knowledge integration.
Results (3)
Baseline performance advantage:
Effective diffusion modeling:
Community and topic dynamics captured:
Research Domain
Cross-platform dynamic social network analysis and knowledge integration