Computational Social Networks is an academic journal published by Springer. (ISSN 2197-4314).
Aims and scope
Computational Social Networks has merged with the Journal of Combinatorial Optimization as of January 2022. All published articles will remain accessible on springer.com.
New submissions relating to the Computational Social Networks should be directed to the Journal of Combinatorial Optimization.
Computational Social Networks showcases refereed papers dealing with all mathematical, computational and applied aspects of social computing. The objective of this journal is to advance and promote the theoretical foundation, mathematical aspects, and applications of social computing. Submissions are welcome which focus on common principles, algorithms and tools that govern network structures/topologies, network functionalities, security and privacy, network behaviors, information diffusions and influence, social recommendation systems which are applicable to all types of social networks and social media.
Topics include (but are not limited to) the following:
Social network design and architecture
Mathematical modeling and analysis
Real-world complex networks
Information retrieval in social contexts, political analysts
Network structure analysis
Network dynamics optimization
Complex network robustness and vulnerability
Information diffusion models and analysis
Security and privacy
Searching in complex networks
Efficient algorithms
Network behaviors
Trust and reputation
Social Influence
Social Recommendation
Social media analysis
Big data analysis on online social networks
This journal publishes rigorously refereed papers dealing with all mathematical, computational and applied aspects of social computing. The journal also includes reviews of appropriate books as special issues on hot topics.
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