Zheng Xiaolong, Zhong Yongguang, Zeng Daniel, Wang Fei-Yue
1State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190 China.
2Department of Management Science and Engineering, Qingdao University, Qingdao, 266071 China.
Front Comput Sci (Berl). 2012;6(5):611-620. doi: 10.1007/s11704-012-1176-1. Epub 2012 Sep 19.
Social networks often serve as a critical medium for information dissemination, diffusion of epidemics, and spread of behavior, by shared activities or similarities between individuals. Recently, we have witnessed an explosion of interest in studying social influence and spread dynamics in social networks. To date, relatively little material has been provided on a comprehensive review in this field. This brief survey addresses this issue. We present the current significant empirical studies on real social systems, including network construction methods, measures of network, and newly empirical results. We then provide a concise description of some related social models from both macro- and micro-level perspectives. Due to the difficulties in combining real data and simulation data for verifying and validating real social systems, we further emphasize the current research results of computational experiments. We hope this paper can provide researchers significant insights into better understanding the characteristics of personal influence and spread patterns in large-scale social systems.
社交网络通常作为信息传播、流行病扩散和行为传播的关键媒介，通过个体之间的共享活动或相似性来实现。最近，我们目睹了对社交网络中社会影响和传播动态研究的兴趣激增。迄今为止，该领域关于全面综述的资料相对较少。本简要调查解决了这一问题。我们展示了当前关于真实社会系统的重要实证研究，包括网络构建方法、网络度量以及新的实证结果。然后，我们从宏观和微观层面的角度对一些相关社会模型进行了简要描述。由于在结合真实数据和模拟数据以验证和确认真实社会系统方面存在困难，我们进一步强调了计算实验的当前研究成果。我们希望本文能为研究人员提供重要见解，以便更好地理解大规模社会系统中个人影响的特征和传播模式。
