A Survey of Cloud Computing and Social Networks <s> Related Work <s> With the increasingly ubiquitous nature of Social networks and Cloud computing, users are starting to explore new ways to interact with, and exploit these developing paradigms. Social networks are used to reflect real world relationships that allow users to share information and form connections between one another, essentially creating dynamic Virtual Organizations. We propose leveraging the pre-established trust formed through friend relationships within a Social network to form a dynamic“Social Cloud”, enabling friends to share resources within the context of a Social network. We believe that combining trust relationships with suitable incentive mechanisms (through financial payments or bartering) could provide much more sustainable resource sharing mechanisms. This paper outlines our vision of, and experiences with, creating a Social Storage Cloud, looking specifically at possible market mechanisms that could be used to create a dynamic Cloud infrastructure in a Social network environment. <s> BIB001 </s> A Survey of Cloud Computing and Social Networks <s> Related Work <s> The research area of Social networks analysis has been recognized as extremely time-consuming tasks as well as large storage space is always necessary in order to store the social data, especially to deal with the data in the World Wide Web. Therefore, how to design an architecture and environment for performing social networks analysis is very essential. In this paper, we proposed a data warehousing and analyzing system which is based on the concept of cloud computing. The system has also been implemented and evaluated under the proposed environment with different cloud computing approaches. <s> BIB002 </s> A Survey of Cloud Computing and Social Networks <s> Related Work <s> Social networking media generate huge content streams, which leverage, both academia and developers efforts in providing unbiased, powerful indications of users' opinion and interests. Here, we present Cloud4Trends, a framework for collecting and analyzing user generated content through microblogging and blogging applications, both separately and jointly, focused on certain geographical areas, towards the identification of the most significant topics using trend analysis techniques. The cloud computing paradigm appears to offer a significant benefit in order to make such applications viable considering that the massive data sizes produced daily impose the need of a scalable and powerful infrastructure. Cloud4Trends constitutes an efficient Cloud-based approach in order to solve the online trend tracking problem based on Web 2.0 sources. A detailed system architecture model is also proposed, which is largely based on a set of service modules developed within the VENUS-C research project to facilitate the deployment of research applications on Cloud infrastructures. <s> BIB003 </s> A Survey of Cloud Computing and Social Networks <s> Related Work <s> Two cutting edge technologies are cloud computing and social media. Healthcare is a promising application of these technologies. In this paper, we describe our design and prototype implementation of a social healthcare network over the cloud. The system is secured with a trust-aware role-based access control. Our work addresses an unmet need in social healthcare networking -- emotional support, and demonstrates social healthcare network application in a real cloud computing environment. <s> BIB004
As social networks and applications reside on the web, cloud computing as an infrastructure or platform is a possible solution for these technologies. Cloud computing presents the same general advantages to social applications: a significant decrease in operational and infrastructure costs, along with the ease of scalability to meet the increasing or decreasing needs of the applications. These advantages would carry over to social network data analysis. With the various cloud resources and services available, the configuration between these technologies can vary. Cloud Computing and social networks have numerous examples of being used together. Typically these involve the social network being hosted on a cloud platform or social applications being hosted on the cloud. Recent research has explored the idea of building cloud infrastructure leaning on the social network for the established relationships and user management it provides. In this type of system, users would provision their own resources or third party resources to other users based upon their previously established relationships in the social network. This type of cloud system would be built on top of existing social network as a social application. The major advantage in this type of configuration would be eschewing the management capabilities off the application and using the existing social networks capabilities BIB001 . With social networks having millions of users and even more user relationships they present large datasets for analysis. As with other data analytic applications, social network analysis can provide useful information about users. This could include things such as sediment analysis, locating key opinion users as well as more targeted applications such as mapping disease outbreaks, and natural disasters. In order to perform these types of analysis, considerable computing power may be required. Once again, cloud computing is a possible solution. Ting et al investigated techniques for cloud based analysis and data warehousing of social networks. Two algorithms were examined: MapReduce and Bulk Synchronous Parallel (BSP). MapReduce is a technique for processing large datasets developed by Google. MapReduce consists primarily of two functions: map and reduce. The map function divides the input and distributes to the nodes that process the data they receive. The reduce function combines and merges those results to generate the output. BSP is a modification of MapReduce using a parallel processing technique. They concluded that the BSP technique performed considerably better than the MapReduce. Although BSP displayed better performance in this case, the ease of use and maturity of existing applications and systems for MapReduce simplifies parallel programming complexity for processing datasets BIB002 . Vokali et al developed a cloud based framework for the analysis of social networking trends. Their framework, Cloud4Trends, adapted and ported trend detection into a cloud application. Additionally their system incorporated status-detection where resources would be increased based upon job completion times. They concluded that the cloud-based social trend detection was a suitable solution given that trend detection is typically a computational intensive process due to the size of the datasets being analyzed. In this way, the amount of resources could be scaled up and down based on their system's needs BIB003 . As with most other technologies, security is of great importance in cloud computing and social networking. Cloud computing security refers to the technology that is used to protect the data and applications of the cloud from threats such as unauthorized access, disruption of services, modification and others. In cloud security, the www.ccsenet.org/nct Network and Communication Technologies Vol. 2, No. 2;  common goals or objectives of information security still apply: confidentiality, integrity, and availability. With social networks attention should be given to the sharing of data between authorized users. Tran et al proposed such a framework for securely sharing data. This was based upon a proxy re-encryption process where a key is shared between both the user and proxy. If a user is removed from a group by the administrator they would be unable to reaccess that group. This model had two weaknesses: security could become vulnerable should the proxy and a user participate in collusion, and the potential load on the proxy for encryption and decryption of data (Tran, 2010) . Wooten et al. developed a social cloud system for healthcare. Once again security is of great concern especially because of the sensitivity of personal health data. They used a trust-aware role based access control system. Trust ratings are calculated based upon the user's activities compared to their peers. Access is allowed based upon these trust ratings and the user's role BIB004 .