The study of social networks originated in the social science, anthropology, and business communities. In recent years, social network research has advanced significantly; the development of advanced techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the internet, the social web, and other large-scale, socio-technical infrastructures, which are widely analyzed using graph theory, statistics, and data mining and machine learning techniques. People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, and community formation and evolution. These trends have led to a rising prominence of SNAM in academia, politics, homeland security, and business.
The international conference on Advances in Social Network Analysis and Mining (ASONAM 2017) will primarily provide an interdisciplinary venue that will bring together practitioners and researchers from a variety of SNAM fields to promote collaborations and exchange of ideas and practices. ASONAM 2017 is intended to address important aspects with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining. The conference solicits experimental and theoretical works reporting original and unpublished research results on social network analysis and mining along with their application to real life situations. More specialized topics within ASONAM 2017 include, but are not limited to:
- Accuracy of network data at scale
- Analysis of covert networks, Dark Web
- Anomaly detection in social network evolution
- Application of social network analysis and mining
- Community discovery and analysis in large scale online/offline social networks
- Computational simulations and modeling
- Crowd sourcing of network data generation and collection
- Cyber anthropology
- Data models for social networks and social media
- Economics of transactions in networks
- Ethics, privacy and security with network data collection and analysis
- Evolution of communities/patterns on the Web and in large organizations
- Impact of social networks on recommendations systems
- Incorporating social information in query processing and query optimization
- Influence of cultural aspects on the formation of communities
- Information acquisition and establishment of social relations
- Information diffusion
- Large-scale graph algorithms for social network analysis
- Migration between communities
- Misbehavior detection in communities
- Multi-actor/multiple-relationship networks
- Network formation and evolution
- Network visualization
- Open source intelligence
- Pattern presentation for end-users and experts
- Personalization for search and for social interaction
- Political impact of social network discovery
- Privacy and security of social networks
- Scalability of social networking/search algorithms
- Social and cultural anthropology
- Social geography and spatial networks
- Statistical modeling of large networks
- Trust in networks
To fully embrace the fast-growing and vigorously dynamic trend of social networks and applications, ASONAM 2017 is eager to consider any breakthroughs in social network analysis and mining in the broadest possible sense.
General areas of interest to ASONAM 2017 include information science and mathematics, communication studies, business and organizational studies, sociology, psychology, anthropology, applied linguistics, biology and medicine.
