Social influence and spread dynamics in social networks

Xiaolong Zheng, Yongguang Zhong, Daniel Zeng, Fei Yue Wang

Research output: Contribution to journalReview articlepeer-review

30 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)611-620
Number of pages10
JournalFrontiers of Computer Science in China
Issue number5
StatePublished - 2012
Externally publishedYes


  • computational experiment
  • social influence
  • social networks
  • spread dynamics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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