An Overview of Approach of Social Computing and Experimental Simulation

In this current article, it is endeavor to explore the possible methods that are from qualitative to quantitative and also combine computer technology to address social system interaction. A distributed paralleled model based on social computing is established to analyze different experiment data and wish to overcome the limitations of complex systems. At the same time, some simulation results will be illustrated in the follow section to further prove the feasibility of experiment. Introduction With the continuous enhancement of the complication of management and social problems, the computational experiments based on artificial society concept are also constantly tried, which is aimed at establishing effective model that could exactly descript social behaviors [1]. Computer experiment methods in the background of different disciplines usually adopt meta-synthesis methodology and combine computer technology, complex system and evolution theory to reappear different scenes of social management activity, which also analyze characteristic behaviors and correlation for further revealing the development rules of social complexity. At the same time, it is not only a state or a social track of simulation systems, but also could be reappeared the internal laws that can’t be seen by human eyes to reveal the evolvement direction of motion of an object. Moreover, although the traditional methods of computational simulation can address a variety of complex systems, it is only a possible mean for the computer experiment methods [2,3]. In foreign research, scholars usually adopt social simulation mode for the study of social problems, which can take reasonable research for society, management and scientific problem complexity and is expected to explore the rules behind of social activity [4]. Social computing methods is used to research complex systems that are composed of society and person, which can not accurately descript their actions, and will bring great challenge to the social computing modeling based on artificial systems. Meanwhile, the study of most social problems is researched by adopting passive observation or statistical methods, which is hard to conduct active experiment for the research objects and accompany by subjective or unobservable factors to make the fact that experiment results do not possess universality [5,6]. In order to solve social computing problems, using artificial systems based on computer is to easily operate and repeat experiment, which could develop well-controlled quantitative analysis for the different impact elements of social computing [7]. Additionally, artificial systems and practice systems simultaneously operate to compose a paralleled system based on social computing, which could reciprocally compare the running process for artificial and actual objects to accomplish effective control and management of the real systems. Actually, the social computing methods based on artificial system no longer are to approach practical complex systems as the sole criterion, but is a replaceable or realizable form [8,9]. The achievement of social computing is strongly associated with the paralleled systems, and it is rather significant that multiple paralleled systems address complex problems to the experiment 7th International Conference on Mechatronics, Computer and Education Informationization (MCEI 2017) Copyright © 2017, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Computer Science Research, volume 75