Advertisement

An Empirical Study of Information Diffusion in Micro-blogging Systems during Emergency Events

  • Kainan Cui
  • Xiaolong Zheng
  • Daniel Dajun Zeng
  • Zhu Zhang
  • Chuan Luo
  • Saike He
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7901)

Abstract

Understanding the rapid information diffusion process in social media is critical for crisis management. Most of existing studies mainly focus on information diffusion patterns under the word-of-mouth spread mechanism. However, to date, the mass-media spread mechanism in social media is still not well studied. In this paper, we take the emergency event of Wenzhou train crash as a case and conduct an empirical analysis, utilizing geospatial correlation analysis and social network analysis, to explore the mass-meida spread mechanism in social media. By using the approach of agent-based modeling, we further make a quantativiely comparison with the information diffusion patterns under the word-of-mouth spread mechanism. Our exprimental results show that the mass-meida spread mechanism plays a more important role than that of the word-of-mouth in the information diffusion process during emergency events. The results of this paper can provide significant potential implications for crisis management.

Keywords

Information diffusion opinion dynamic emergency response social media micro-blogging systems 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Adam, N.R., Shafiq, B., Staffin, R.: Spatial Computing and Social Media in the Context of Disaster Management. IEEE Intelligent Systems 27, 90–96 (2012)CrossRefGoogle Scholar
  2. 2.
    Daniel, Z., Hsinchun, C., Lusch, R., Shu-Hsing, L.: Social Media Analytics and Intelligence. IEEE Intelligent Systems 25, 13–16 (2010)CrossRefGoogle Scholar
  3. 3.
    Zeng, D., Wang, F.-Y., Carley, K.M.: Guest Editors’ Introduction: Social Computing. IEEE Intelligent Systems 22, 20–22 (2007)zbMATHGoogle Scholar
  4. 4.
    Tyshchuk, Y., Wallace, W.A.: Actionable Information during Extreme Events – Case Study: Warnings and 2011 Tohoku Earthquake. In: Conference Actionable Information during Extreme Events – Case Study: Warnings and 2011 Tohoku Earthquake, pp. 338–347 (2012)Google Scholar
  5. 5.
    Culotta, A.: Towards detecting influenza epidemics by analyzing Twitter messages. In: Proceedings of the First Workshop on Social Media Analytics, pp. 115–122. ACM, Washington D.C (2010)CrossRefGoogle Scholar
  6. 6.
    Cui, K., Cao, Z., Zheng, X., Zeng, D., Zeng, K., Zheng, M.: A Geospatial Analysis on the Potential Value of News Comments in Infectious Disease Surveillance. In: Chau, M., Wang, G.A., Zheng, X., Chen, H., Zeng, D., Mao, W. (eds.) PAISI 2011. LNCS, vol. 6749, pp. 85–93. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  7. 7.
    Il-Chul, M., Oh, A.H., Carley, K.M.: Analyzing social media in escalating crisis situations. In: Conference Analyzing Social Media in Escalating Crisis Situations, pp. 71–76 (2011)Google Scholar
  8. 8.
    Bass, F.M.: Comments on “A New Product Growth for Model Consumer Durables The Bass Model”. Management Science 50, 1833–1840 (2004)CrossRefGoogle Scholar
  9. 9.
    Zheng, X., Zhong, Y., Zeng, D., Wang, F.-Y.: Social influence and spread dynamics in social networks. Front. Comput. Sci. 6, 611–620 (2012)MathSciNetGoogle Scholar
  10. 10.
    Kim, M., Xie, L., Christen, P.: Event Diffusion Patterns in Social Media. In: Conference Event Diffusion Patterns in Social Media (2012)Google Scholar
  11. 11.
    Zheng, X., Zeng, D., Li, H., Wang, F.: Analyzing open-source software systems as complex networks. Physica A: Statistical Mechanics and its Applications 387, 6190–6200 (2008)CrossRefGoogle Scholar
  12. 12.
    Toole, J.L., Cha, M., González, M.C.: Modeling the Adoption of Innovations in the Presence of Geographic and Media Influences. PLoS ONE 7,e29528 (2012)Google Scholar
  13. 13.
    Watts, D.J., Dodds, P.S.: Influentials, Networks, and Public Opinion Formation. Journal of Consumer Research 34, 441–458 (2007)CrossRefGoogle Scholar
  14. 14.
    Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a social network or a news media? In: Proceedings of the 19th International Conference on World Wide Web, pp. 591–600. ACM, Raleigh (2010)CrossRefGoogle Scholar
  15. 15.
    Xu, X.: Internet Facilitated Civic Engagement in China’s Context: A Case Study of the Internet Event of Wenzhou High-speed Train Accident (2011)Google Scholar
  16. 16.
    Watts, D.J., Strogatz, S.H.: Collective dynamics of /‘small-world/’ networks. Nature 393, 440–442 (1998)CrossRefGoogle Scholar
  17. 17.
    Pengyi, F., Pei, L., Zhihong, J., Wei, L., Hui, W.: Measurement and analysis of topology and information propagation on Sina-Microblog. In: Conference Measurement and Analysis of Topology and Information Propagation on Sina-Microblog, pp. 396–401 (2011)Google Scholar
  18. 18.
    Thelwall, M.: Homophily in MySpace. Journal of the American Society for Information Science and Technology 60, 219–231 (2009)CrossRefGoogle Scholar
  19. 19.
    Moran, P.A.: The interpretation of statistical maps. Journal of the Royal Statistical Society. Series B (Methodological) 10, 243–251 (1948)MathSciNetzbMATHGoogle Scholar
  20. 20.
    Li, X., Mao, W., Zeng, D., Wang, F.-Y.: Agent-Based Social Simulation and Modeling in Social Computing. In: Yang, C.C., et al. (eds.) ISI Workshops 2008. LNCS, vol. 5075, pp. 401–412. Springer, Heidelberg (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Kainan Cui
    • 1
    • 2
  • Xiaolong Zheng
    • 2
    • 3
  • Daniel Dajun Zeng
    • 2
  • Zhu Zhang
    • 2
  • Chuan Luo
    • 2
  • Saike He
    • 2
  1. 1.The School of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’anChina
  2. 2.The State Key Laboratory of Management and Control for Complex Systems, Institute of AutomationChinese Academy of SciencesBeijingChina
  3. 3.Dongguan Research Institute of CASIA, Cloud Computing CenterChinese Academy of SciencesDongguanChina

Personalised recommendations