Research On Key Technologies Of Visual Analysis Of Social Network Based On Mobile Cloud

Now is in the mobile Internet era of rapid development, as smart phone, tablet PC and other mobile terminals used more and more widely, users have urgent need to use visual analysis application on mobile platform; On the other hand, along with the popularity of mobile Internet, more and more users tend to participate in social activities on mobile device. However, the mobile device is limited by compute ability, storage ability and screen size, and it has unique interactive ways, so, the visual analysis method of social network on PC can’t be applied to the mobile platform simply. Therefore, the research on key technology of visual analysis of social network based on mobile cloud computing has important theoretical and practical value.This thesis uses the social network as visual object, and aimed at theoretical research on how to obtain good user experience of visual analysis application on mobile device which is limited by resources such as compute ability, storage ability and screen size. Based on the related research achievements at home and abroad, the main work of this thesis deploys from the following several aspects:(1) Designing data analytical model based on the mobile cloud. Using Deep Web crawler technology and OAuth authentication technology to get data from social network, and analyzing the structure of the data, combining with HDFS technology and MapReduce technology in Hadoop to design data analytical model based on the mobile cloud, parsing user original data as data format that can be visualized, to solve the problem what is mobile device is limited by compute ability and storage ability.(2) Realizing the social network layout algorithm based on the particle swarm optimization for the mobile platform. Studying on the layout algorithm based on the force directed model, analyzing the disadvantages of the class of layout algorithm in social work visualization application, then analyzing the particle swarm optimization algorithm, to translate the node layout problem to constrained optimization problem, and combining with the subgroup characteristics of social network, realizing social network layout algorithm based on particle swarm optimization, to solve the problem what is mobile device is limited to screen size.(3) Designing the interactive model of visual analysis based on mobile terminal. Analyzing the data transmission strategy that used commonly on mobile platform, choosing JSON data transmission format which is suited to visual analysis, then according to the character of the mobile platform, use SVG technology for data visualization based on HTML5, and analyzing the interactive mode of mobile platform and interactive patterns of visual analysis, designing the interactive model of visual analysis based on mobile terminal, in order to help users to present and understand social network data on mobile device better.Through the design of prototype system, realized the data analysis model and visual interaction model which is proposed by this thesis, and verified the validity of layout algorithm designed in this paper. The results show that the scheme given in this thesis has feasibility for social network visual analysis application on mobile platform, and can obtain good user experience.