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. .