It is our pleasure to invite you to participate in the First Workshop on Cloud Computing on Social Network (CCSN 2011) that is held as a part of the International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2011).
Cloud computing and social networks are two of the more powerful movements in the web 2.0 space. So the potential of social media and the cloud integrating is compelling to say the least. Salesforce.com recently rolled out the Service Cloud, a customer service application that tries to capture the crowd sourced pools of knowledge floating across the internet from sites like Google, Facebook and Amazon, and then uses this information to better equip commercial customer service operations with useful knowledge.
Additionally, the cloud computing have now becoming a very popular research area not only for data mining, pattern reorganization and web mining but also social network analysis. Cloud computing is a concept that has the ability to process and analyze large amount of data and by this to discover valuable information from the data. In recent year, due to the growth of cloud computing architecture, social communications and social networking websites in finance domain, data mining and pattern reorganization becomes a very important and powerful technique to process and analyze such large amount of data.
The workshop aims at promoting the exchange of ideas in this research area. It is therefore also valuable to include a workshop about this topic in this year CCSN conference.
This workshop invites papers of the following topics, but never exclusive:
• Cloud Computing in Social Network
• Cloud Application in Social Network
• Cloud Infrastructure in Social Network
• Cloud Framework in Social Network
• Cloud Service in Social Network
• Infrastructure as a Service (IaaS) for Social Network
• Platform as a Service (PaaS) for Social Network
• Software as a Service (SaaS) for Social Network
• Intelligent and Multi-agent based Decision Support Systems
• Cloud Computing for Social Finance Network
• Experiment and Implementation
• Case Studies and Empirical Studies