It is our pleasure to invite you to submit your paper to this special issue. This special issue is devoted to analysis of these large-scale social structures. Complex social networks can be analysed from either static or dynamic perspective, making those complex structures even more challenging for investigation. On one hand, we are looking for original contributions to the fundamental research of complex networks (e.g., diffusion, measures and their dynamics, and multirelational aspects). On the other hand, we also seek for business and industrial applications of social network analysis that help to solve real-world problems.

Social networks have been investigated for many years but the scope of the analyses was limited due to the small data samples that could be collected using questionnaires and interviews. Because of that there was no time efficiency requirement that used methods should meet. Nowadays, this situation changes as we have at our disposal vast amount of data about people and their interactions. This data comes from technological-based services such as online social networking sites, telecommunication services, and email systems. Also, from the sociological perspective much more data can be collected. Simple online surveys enable us to easily reach broader audience. From this vast amount of data we are able to extract and analyse the social networks that consist of millions of nodes and connections. Based on this data we are able to build new network models that enable to better capture real-world phenomena (e.g., stochastic block models).

Due to scale, complexity, and dynamics, these networks are extremely difficult to analyse in terms of traditional social network analysis methods that are not optimised in terms of performance. In the same time, data about human activities provides new opportunities for new applications.

The area of social network analysis and its applications bring together researchers and practitioners from different fields and the main goal of this special issue is to provide them the opportunity to share their visions, research achievements, and solutions as well as establishing worldwide cooperative research and development. At the same time, we want to provide a platform for discussing research topics underlying the concepts of complex social network analysis and its applications by inviting members of different communities that share this common interest of investigating social networks. As the area of social networks is a highly cross-disciplinary one, we aim to foster and develop sustainable collaborations between computer science and informatics, sociology, cognitive science and psychology, geographic and environmental science, biology, health, and social sciences. This will give the opportunity to push further the discussion upon the potential of social networks and their applications across these communities.

Potential topics include but are not limited to the following:

• Data science of complex social networks
• Information/opinion/knowledge spread and modelling
• Complex social networks modelling approaches
• Multilayer complex social networks
• Complexity methodologies in the context of social network analysis
• Dynamics and predictive modelling of complex social networks
• Dynamic social network and event streams analysis
• Trust and reputation in complex social networks
• Social media
• Business/e-business/e-commerce
• Customer relationship management
• Social networks in health and social care
• Educational applications/e-learning
• Collaborative information retrieval
• Crime detection and investigation
• Collaborative environments, including wikis and other sharing systems
• Virtual worlds and online multiplayer games
• Systems for e-society, including e-government
• User analysis in web-based systems
• Applications of spatiotemporal, textual, dynamic, and multilayer models
• Recommender systems and collaborative filtering in complex networks