Foundation Models for Social Network Analysis

This special issue seeks to unite researchers in the development of foundation models tailored for Social Network Analysis (SNA). The objective is to enhance the efficiency, accuracy, and understanding of SNA systems, enabling users to navigate and analyze intricate social networks effectively. Anticipated outcomes include improved accuracy in network analysis, efficient extraction of meaningful patterns, and enhanced adaptability for diverse social scenarios. Contributions are invited on diverse aspects of foundation models for Social Network Analysis, encompassing but not limited to: • Novel datasets and benchmarks for building domain-specific foundation models for SNA • Foundation models for predicting social network dynamics • Foundation models for community detection in social networks • Foundation models for sentiment analysis in social media • Foundation models for influence prediction in social networks • Multimodal data analysis with foundation models in the social context • Large-scale data processing with foundation models • Pre-training techniques tailored for social network analysis • Fine-tuning strategies for foundation models • Prompt engineering techniques for foundation models • Transfer learning techniques for SNA foundation models • Domain adaptation techniques for SNA foundation models • Domain-specific foundation models for social networks (e.g., temporal networks, online communities) • Systems and applications based on foundation models in SNA