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Applications

  • Haiyan Wang
  • Feng Wang
  • Kuai Xu
Chapter
  • 36 Downloads
Part of the Surveys and Tutorials in the Applied Mathematical Sciences book series (STAMS, volume 7)

Abstract

In this chapter we present two applications of partial differential equation models for information diffusion in online social networks. We present a diffusion-advection PDE model to describe a transnational diffusion process of social movement in social media during the Egyptian revolution in 2011. We develop a PDE-based influenza surveillance system by analyzing flu related Twitter data. The system aims to predict flu trends at more localized levels by leveraging the availability of geocoded Twitter data.

References

  1. 1.
    Achrekar, H., Gandhe, A., Lazarus, R., Yu, S.-H., Liu, B.: Predicting flu trends using twitter data. In: 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pp. 702–707. IEEE, Piscataway (2011)Google Scholar
  2. 2.
    Achrekar, H., Gandhe, A., Lazarus, R., Yu, S.-H., Liu, B.: Twitter improves seasonal influenza prediction. In: International Conference on Health Informatics (HEALTHINF), pp. 61–70 (2012)Google Scholar
  3. 22.
    Cook, S., Conrad, C., Fowlkes, A.L., Mohebbi, M.H.: Assessing Google flu trends performance in the United States during the 2009 influenza virus a (H1N1) pandemic. PLoS One 6, e23610 (2011)CrossRefGoogle Scholar
  4. 63.
    Kwon, K., Wang, H., Xu, W., Raymond, R.: A spatiotemporal model of Twitter information diffusion: an example of Egyptian revolution 2011. In: Proceedings of Social Media and Society, ACM International Conference Proceeding Series (ICPS), July 27–29, Toronto (2015)Google Scholar
  5. 64.
    Kwon, K., Xu, W., Wang, H., Chon, J.: Spatiotemporal diffusion modeling of global mobilization in social media: the case of Egypt revolution 2011. Int. J. Commun. 10, 73–97 (2016)Google Scholar
  6. 74.
    Logan, J.D.: Transport Modeling in Hydrogeochemical Systems. Spinger, New York (2001)CrossRefGoogle Scholar
  7. 93.
    Oh, O., Kwon, K., Rao, H.: An exploration of social media in extreme events: rumor theory and Twitter during the Haiti earthquake 2010. In: Proceedings of the International Conference on Information Systems, St. Louis, pp. 12–15 (2010)Google Scholar
  8. 117.
    Takahashi, L., Maidana, N., Ferreira, W., Pulino, P., Yang, H.: Mathematical models for the Aedes aegypti dispersal dynamics: travelling waves by wing and wind. Bull. Math. Biol. 67, 509–528 (2005)MathSciNetCrossRefGoogle Scholar
  9. 118.
    Takhteyeva, Y., Gruzdb, A., Wellman, B.: Geography of Twitter networks. Soc. Netw. 34, 73–81 (2012)CrossRefGoogle Scholar
  10. 131.
    Wang, F., Wang, H., Xu, K., Raymond, R., Chon, J.,Fuller, S., Debruyn, A.: Regional level influenza study with geo-tagged Twitter data. J. Med. Syst. 40, 189 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Haiyan Wang
    • 1
  • Feng Wang
    • 1
  • Kuai Xu
    • 1
  1. 1.School of Mathematical & Natural SciencesArizona State UniversityPhoenixUSA

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