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Social influence and spread dynamics in social networks

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Abstract

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.

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Authors and Affiliations

  1. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Xiaolong Zheng, Daniel Zeng & Fei-Yue Wang

  2. Department of Management Science and Engineering, Qingdao University, Qingdao, 266071, China

    Yongguang Zhong

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  1. Xiaolong Zheng
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Correspondence to Fei-Yue Wang.

Additional information

Xiaolong Zheng is an assistant professor in the State Key Laboratory of Management and Control for Complex Systems at the Institute of Automation of the Chinese Academy of Sciences. His research interests include complex networks, social computing, and data mining. Specifically, he is interested in social dynamics, social influence, spread dynamics, and opinion and behavior mining in social media.

Yongguang Zhong is a professor in the Department of Management Science and Engineering at Qingdao University in China. His current research interests include system dynamics, operations management, and reverse logistics.

Daniel Zeng is a professor in the State Key Laboratory of Management and Control for Complex Systems at the Institute of Automation of the Chinese Academy of Sciences. His research interests include multi-agent systems, collaborative information and knowledge management, recommender systems, and automated negotiations and auctions. Specifically, he is interested in social computing, information and security informatics, spatio-temporal data analysis, and online surveillance.

Fei-Yue Wang is a professor in the State Key Laboratory of Management and Control for Complex Systems at the Institute of Automation of the Chinese Academy of Sciences. His current research interests include social computing, parallel control and management, web and services science, and agent-based intelligent systems.

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Zheng, X., Zhong, Y., Zeng, D. et al. Social influence and spread dynamics in social networks. Front. Comput. Sci. 6, 611–620 (2012). https://doi.org/10.1007/s11704-012-1176-1

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