Open Source Social Network Simulator Focusing on Spatial Meme Diffusion

  • Xinyue Ye
  • Lanxue Dang
  • Jay Lee
  • Ming-Hsiang Tsou
  • Zhuo Chen
Part of the Human Dynamics in Smart Cities book series (HDSC)


It is crucial to discover, track, summarize, and even predict popular topics and events occurring in the social network in the space-time context. At the same time, it is very useful that a series of “what if” scenarios can be developed to estimate the meme diffusion. However, spatial social scientists have been slow to adopt and implement new methods for social media data analysis due to the lack of open source software packages, which become a major impediment to the promotion of human dynamics research. The availability and widespread use of source codes will play a critical role in the adoption of new perspectives and ideas enhancing spatial social network analytics. The proposed Open Source Social Network Simulator implements the methodological advances in an open source environment of Python for exploring spatial meme diffusion, using twitter data as the case study. The methods are built in open source environments and thus are easily extensible and customizable. The open source movement can also facilitate the explosion of the social media analytics routines by increasingly easier development processes with powerful scripting language environments.



This material is based upon work supported by the National Science Foundation under Grant No. 1416509 and 1637242.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Xinyue Ye
    • 1
  • Lanxue Dang
    • 2
  • Jay Lee
    • 1
  • Ming-Hsiang Tsou
    • 3
  • Zhuo Chen
    • 1
  1. 1.Department of GeographyKent State UniversityKentUSA
  2. 2.Department of Computer ScienceHenan UniversityKaifengChina
  3. 3.Department of GeographySan Diego State UniversitySan DiegoUSA

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