Skip to main content

Mathematical Model of Hit Phenomena as a Theory for Human Interaction in the Society

  • Conference paper
Complex Sciences (Complex 2012)

Abstract

A mathematical model for the hit phenomenon in entertainment within a society is presented as a stochastic process of interactions of human dynamics. The model uses only the time distribution of advertisement budget as an input, and word-of-mouth (WOM) represented by posts on social network systems is used as data to compare with the calculated results. The unit of time is a day. The calculations for the Japanese motion picture market based on to the mathematical model agree very well with the actual residue distribution in time.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Allsop, D.T., Bassett, B.R., Hoskins, J.A.: J. Advertising Research 47, 398 (2007)

    Article  Google Scholar 

  2. Kostka, J., Oswald, Y.A., Wattenhofer, R.: Word of Mouth: Rumor Dissemination in Social Networks. In: Shvartsman, A.A., Felber, P. (eds.) SIROCCO 2008. LNCS, vol. 5058, pp. 185–196. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  3. Bakshy, E., Hofman, J.M., Mason, W.A., Watts, D.J.: Proceedings of the Fourth ACM International Conference on Web Search and Data Mining

    Google Scholar 

  4. Jansen, B.J., Zhang, M., Sobel, K., Chowdury, A.: J. Am. Soc. Inform. Sci. Tech. 60, 2169 (2009)

    Article  Google Scholar 

  5. Brown, J.J., Reingen, P.H.: Journal of Consumer Research 14, 350 (1987)

    Article  Google Scholar 

  6. Murray, K.: Journal of Marketing 55, 10 (1991)

    Article  Google Scholar 

  7. Banerjee, A.: Quarterly Journal of Economics 107, 797 (1992)

    Google Scholar 

  8. Taylor, J.: Brandweek, 26 (June 2, 2003)

    Google Scholar 

  9. Ishii, A., Arakaki, H., Matsuda, N., Umemura, S., Urushidani, T., Yamagata, N., Yoshida, N.: New Journal of Physics 14, 063018 (22pp) (2012)

    Google Scholar 

  10. Ishii, A., Matsumoto, T., Miki, S.: Prog. Theor. Phys. (suppl. 194), 64–72 (2012)

    Google Scholar 

  11. Elberse, A., Eliashberg, J.: Marketing Science 22, 329 (2003)

    Article  Google Scholar 

  12. Liu, Y.: Journal of Marketing 70, 74 (2006)

    Article  Google Scholar 

  13. Duan, W., Gu, B., Whinston, A.B.: Decision Support Systems 45, 1007 (2008)

    Article  Google Scholar 

  14. Duan, W., Gu, B., Whinston, A.B.: J. Retailing 84, 233 (2008)

    Article  Google Scholar 

  15. Zhu, M., Lai, S.: Proceeding of the 2009 International Conference on Electronic Commerce and Business Intelligence

    Google Scholar 

  16. Goel, S., Hofman, J.M., Lahaie, S., Pennock, D.M., Watts, D.J.: PNAS 107, 1786 (2010)

    Google Scholar 

  17. Karniouchina, E.V.: International Journal of Research in Marketing 28, 62 (2011)

    Article  Google Scholar 

  18. Sinha, S., Raghavendra, S.: Eur. Phys. J. B42, 293 (2004)

    Article  Google Scholar 

  19. Pan, R.K., Sinha, S.: New J. Phys. 12, 115004 (2010)

    Article  Google Scholar 

  20. Asur, S., Huberman, R.A.: aiXiv:1003.5699v1

    Google Scholar 

  21. Ratkiewicz, J., Fortunato, S., Flammini, A., Menczer, F., Vespignani, A.: Phys. Rev. Lett. 105, 158701 (2010)

    Article  Google Scholar 

  22. Eliashberg, J., Jonker, J.-J., Sawhney, M.S., Wierenga, B.: Marketing Science 19, 226 (2000)

    Article  Google Scholar 

  23. Bass, F.M.: Management Science 15, 215–227 (1969)

    Article  Google Scholar 

  24. Bass, F.M.: The Adoption of a Marketing Model: Comments and Observations. In: Mahajan, V., Wind, Y. (eds.) Innovation Diffusion Models of New Product Acceptance. Ballinger (1986)

    Google Scholar 

  25. Dellarocas, C., Awad, N.F., Zhang, X.: Working paper. MIT Sloan School of Management (2004)

    Google Scholar 

  26. Dellarocas, C., Zhang, X., Awad, N.F.: J. Interactive Marketing 21(4), 23–45 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Ishii, A., Koguchi, H., Uchiyama, K. (2013). Mathematical Model of Hit Phenomena as a Theory for Human Interaction in the Society. In: Glass, K., Colbaugh, R., Ormerod, P., Tsao, J. (eds) Complex Sciences. Complex 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 126. Springer, Cham. https://doi.org/10.1007/978-3-319-03473-7_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-03473-7_14

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03472-0

  • Online ISBN: 978-3-319-03473-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics