Scope

Network Science is a rapidly growing interdisciplinary field with contributions stemming from different disciplines, both theoretical and applied. In addition, Big Data, especially represented as graphs or networks, is rapidly becoming available from different complex systems such social systems, web systems, information systems, biological systems, transportation systems or physical systems. Moreover, a number of these systems interact, creating multi-scale or multi-modal graphs and networks, presenting new challenges for modeling and understanding. The specialty section Big Data Networks welcomes submissions that are at the bring forth model-driven or data-driven approaches to studying networks or graphs in different complex systems. The submissions may cover new methods that enable statistical or machine learning based modeling of graphs / networks, or open up new observations and insights about a complex system. This section especially welcomes papers that demonstrate societal impact. The topics of interest include, but not limited to:

• Graph Mining
• Network Science
• Statistical Relational Learning
• Complex Systems
• Learning on Graphs
• Computational Social Science
• Social Networks
• Information Networks
• Transportation Systems
• Biological Systems
• Network Medicine
• Recommendation Systems
• Influence and Information Propagation
• Deep Learning and Embedding Methods
• Ethics, Fairness, Trust and Networks

Submissions to Big Data Networks are no longer possible via Frontiers in Digital Humanities, as this field journal is now closed. This section still welcomes submissions via Frontiers in Big Data.

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