For more than a century, social networks have been studied in a variety of disciplines including sociology, anthropology, psychology, and economics. The Internet, the social Web, and other large-scale, socio-technological infrastructures have triggered a growing interest and significant methodological advancements in social network analysis and mining. Method development in graph theory, statistics, data mining and machine learning, and statistical mechanics is inspired by new research problems and, in turn, opens up further possibilities for application. These spiraling trends have led to a rising prominence of social network analysis and mining methods and tools in academia, politics, security, and business.
The international conference series on Advances in Social Network Analysis and Mining (ASONAM 2023) provides an interdisciplinary venue that brings together researchers and practitioners from a broad variety of fields to promote collaborations and exchange of ideas and practices. ASONAM 2023 is intended to address important aspects with a specific focus on emerging trends and industry needs. The conference solicits empirical, experimental, methodological, and theoretical research reporting original and unpublished results on social network analysis and mining along with applications.

Techniques	Problems	Application domains
Data collection and quality	Centrality and roles	Attributed networks
Big data and scalability	Community detection	Online and offline social networks
Deep learning and embeddings	Link prediction	Multirelational, multidimensional, multi-aspect, multilayer networks
Statistical learning	Information diffusion	Feature-rich networks
Algorithms and techniques	Influence propagation	Time-evolving networks
Visualization	Anomaly detection	Probabilistic networks
Modeling and simulation	Network macro structures	Semantic networks
Explainable network analysis	Network evolution	Social geography and spatial Networks
	Emergence	Social, cultural, and cyber anthropology
	Privacy and security	Policy impact and analysis
	Collective behavior	Networks in biology and ecology
	Crowd sourcing	Digital Humanities
	Social Recommender Systems
	Misinformation and Misbehavior Analysis and Detection
	Reputation and Trust in Social Networks
	Fairness Bias and Transparency in Social Media