My Journal Platforms of Interest

Computational Social Networks

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

Journal of Big Data

The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems.

Open article collection

Big Data and Smart Computing– potential topics include, but are not limited to:

• Techniques and models for network science and big data
• Algorithms and systems for network science and big data
• Databases and data mining for network science and big data
• Graph mining and opinion mining
• Bioinformatics data management
• Infrastructure and platform for smart computing
• Mobile smartphone applications
• Big data analytics and social media
• Parallel and distributed computing for network science and big data
• Cloud and grid computing
• Smart devices and hardware
• Smart location-based services

Deadline for submissions: 1 October 2016

Social Network Analysis and Mining (SNAM)

A multidisciplinary journal serving researchers and practitioners in academia and industry.  The main areas covered by SNAM include:

• data mining advances on the discovery and analysis of communities, personalization for solitary activities (e.g. search) and social activities (e.g. discovery of potential friends), the analysis of user behavior in open forums (e.g. conventional sites, blogs and forums) and in commercial platforms (e.g. e-auctions), and the associated security and privacy-preservation challenges;
• social network modeling, construction of scalable and customizable social network infrastructure, identification and discovery of complex, dynamics, growth, and evolution patterns using machine learning and data mining approaches or multi-agent based simulation;
• social network analysis and mining for open source intelligence and homeland security. Papers should elaborate on data mining and machine learning or related methods, issues associated to data preparation and pattern interpretation, both for conventional data (usage logs, query logs, document collections) and for multimedia data (pictures and their annotations, multi-channel usage data).

Topics include but are not limited to:

• Applications of social network in business engineering, scientific and medical domains, homeland security, terrorism and criminology, fraud detection, public sector, politics, and case studies
• Anomaly and outlier detection in social networks
• Behavior and identity detection and monitoring
• Community discovery in large-scale and complex social networks
• Contextual social network analysis
• Data models and query models for social networks and social media
• Data preparation for social network analysis and mining
• Data protection inside communities
• Dynamics and evolution patterns of social networks, trend prediction
• Evolution of communities in the Web Information acquisition and establishment of social relations
• Large-scale graph algorithms
• Link and node prediction in social networks
• Misbehaviour detection in communities
• Mobile and stream data analysis for social network applications
• Multi-agent based social network modeling and analysis
• Multidisciplinary applications of social network analysis
• Network integration and conflict resolution
• Online social networking and human computer interaction
• Pattern presentation for end-users and experts
• Personalization for search and for social interaction
• Recommendations for e-commerce and business applications
• Recommendation networks
• Search algorithms on social networks
• Security and privacy in social networks
• Social media monitoring and analysis
• Spatio-temporal aspects in social networks and social media
• Tools and infrastructures for social networking platforms Web 2.0 and Web communities