Social network analysis is the study of relationships between social entities, a field significantly enriched by the recent advances in internet technologies and social media platforms such as Facebook, Twitter, and LinkedIn. These platforms offer unprecedented opportunities for individuals to connect, communicate, and share their perspectives on a vast array of topics. The dynamic and ever-evolving nature of social networks, coupled with the massive scale of user participation, poses significant challenges for researchers, particularly in data mining and machine learning. The International Conference on Social Networks Analysis, Management and Security (SNAMS-2025) aims to provide a comprehensive forum for researchers, practitioners, and industry experts to present and discuss their latest findings and innovations in the realm of social network analysis. This conference seeks to explore the vast opportunities in social networks, addressing both theoretical and practical challenges. SNAMS-2025 is dedicated to fostering an environment where students, scientists, engineers, and researchers can exchange ideas, present novel research contributions, and share experiences across all facets of social networks. We invite original research contributions in a wide range of topics, including but not limited to:
Data mining and machine learning techniques for social networks
Social network dynamics and evolution
Security, privacy, and trust in social networks
Analysis of social media content and trends
Impact of social networks on society and human behavior
Network visualization and big data analytics
Applications of social network analysis in various domains (e.g., marketing, healthcare, education)
Algorithms and models for social network analysis
Sentiment analysis and opinion mining in social media
Influence and information propagation in social networks
Industrial applications of social network analysis
Big data technologies for social network analysis
Cloud and edge analytics for social networks
Semantic analysis and knowledge graphs in social networks
Business intelligence and decision-making based on social network data
Ethical issues and governance in social network analysis
Real-time and streaming analytics for social networks
Case studies and best practices in social network management
Integration of social network analysis with IoT and smart environments
Fakenews detection
Bots and social media
Artificial Intelligence and Machine Learning for Social Networks Analyis
also topics include the following
SYSTEMS & INFRASTRUCTURE
Systems and algorithms for social search
Infrastructure support for social networks and systems
Dynamics and evolution patterns of large and complex networks
Social properties in systems design
Learnings from operational social networks
Data Collection
Big Data and Social Paradigms
ALGORITHMS AND MODELS
Deep Learning and Knowledge Discovery.
Measurement and analysis of social and crowdsourcing systems
Benchmarking, modeling, performance and workload characterization
Modeling Social Networks and behavior
Management of social network data
Streaming algorithms for social data
Knowledge and innovation networks
Methods for social and media analysis
Models for network data
Network analysis in human and social sciences
Information propagation and assimilation in social networks
Data mining and machine learning in social systems
APPLICATIONS
Novel social applications and systems
Transient OSNs (e.g. Snapchat)
Special purpose OSNs (e.g., Instagram, Vine)
Communities in social networks
Collaboration networks
New models of advertising and monetization in social networks
Mobile advertising on OSNs
Network visualization
Social networks and online education
Sentiment analysis on OSNs
Multilingual social networks
Social networks as agents of societal change
PRIVACY & SECURITY
Privacy and security in social systems
Trust and reputations in social systems
Detection, analysis, prevention of spam, phishing, and misbehavior in social systems