Skip to main content
SpringerLink
Log in

Statistics of co-occurring keywords in confined text messages on Twitter

  • Regular Article
  • Published:
The European Physical Journal Special Topics Aims and scope Submit manuscript

Abstract

Online social media such as the micro-blogging site Twitter has become a rich source of real-time data on online human behaviors. Here we analyze the occurrence and co-occurrence frequency of keywords in user posts on Twitter. From the occurrence rate of major international brand names, we provide examples of predictions of brand-user behaviors. From the co-occurrence rates, we further analyze the user-perceived relationships between international brand names and construct the corresponding relationship networks. In general the user activity on Twitter is highly intermittent and we show that the occurrence rate of brand names forms a highly correlated time signal.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. A.L. Barabasi, Nature 435(7039), 207 (2005)

    Article  ADS  Google Scholar 

  2. A. Vázquez, J.G. Oliveira, Z. Dezsö, K.I. Goh, I. Kondor, A.L. Barabási, Phys. Rev. E 73, 036127 (2006)

    Article  ADS  Google Scholar 

  3. J. Mathiesen, L. Angheluta, P.T. Ahlgren, M.H. Jensen, Proc. Natl. Acad. Sci. 110, 17259 (2013)

    Article  ADS  Google Scholar 

  4. J. Ratkiewskicz, S. Fortunato, F. Flammini, A. Vespignani, Phys. Rev. Lett. 105, 158701 (2010)

    Article  ADS  Google Scholar 

  5. J. Leskovec, M. McGlohon, C. Faloutsos, N. Glance, M. Hurst, Proc. SIAM Int. Conf. on Data Mining (SDM) (2007)

  6. B. Gonalves, J.J. Ramasco, Phys. Rev. E 78, 026123 (2008)

    Article  ADS  Google Scholar 

  7. D. Helbing, I. Farkas, T. Vicsek, Nature 407, 487 (2000)

    Article  ADS  Google Scholar 

  8. D. Helbing, A. Johansson, J. Mathiesen, M.H. Jensen, A. Hansen, Phys. Rev. Lett. 97, 168001 (2006)

    Article  ADS  Google Scholar 

  9. R. Donangelo, M.H. Jensen, I. Simonsen, K. Sneppen, J. Stat. Mech.: Theory Exper. 2006, L11001 (2006)

    Article  Google Scholar 

  10. J.O. Haerter, B. Jamtveit, J. Mathiesen, Phys. Rev. Let. 109, 168701 (2012)

    Article  ADS  Google Scholar 

  11. J. Kulshrestha, F. Kooti, A. Nikravesh, P.K. Gummadi, Geographic Dissection of the Twitter Network. In ICWSM (2012)

  12. A. Mislove, S. Lehmann, Y.Y. Ahn, J.P. Onnela, J.N. Rosenquist, Understanding the Demographics of Twitter Users. In ICWSM (2011)

  13. H. Choi, H. Varian, Econom. Record 88, 2 (2012)

    Article  Google Scholar 

  14. J. Bollen, H. Mao, H., X. Zeng, J. Comput. Sci. 2, 1 (2011)

    Article  Google Scholar 

  15. X. Zhang, H. Fuehres, P.A. Gloor, Proc.-Social Behav. Sci. 26, 55 (2011)

    Article  Google Scholar 

  16. S. Asur, B.A. Huberman (2010, August), Predicting the future with social media. In Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on Vol. 1, IEEE, p. 492

  17. H. Kwak, C. Lee, H. Park, S. Moon, What is Twitter, a social network or a news media? Proceedings of the 19th international conference on World Wide Web (2010), p 591

  18. M. Rosvall, C.T. Bergstrom, Proc. Natl. Acad. Sci. 105, 1118 (2008)

    Article  ADS  Google Scholar 

  19. J. Mathiesen, P. Yde, M.H. Jensen, Scient. Rep. 2 (2012)

  20. M. Steyvers, J.B. Tenenbaum, Cognit. Sci. 29, 4178 (2005)

    Google Scholar 

  21. C. Cattuto, A. Barrat, A. Baldassarro, G. Schehr, V. Loreto, Proc. Natl. Acad. Sci. USA 26, 10511 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Niels Bohr Institute, University of Copenhagen, Blegdamsvej 17, 2100, Copenhagen, Denmark

    J. Mathiesen & M. H. Jensen

  2. Physics of Geological Processes, Department of Physics, University of Oslo, PO 1048, Blindern, 0316, Oslo, Norway

    L. Angheluta

Authors
  1. J. Mathiesen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. L. Angheluta
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. H. Jensen
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mathiesen, J., Angheluta, L. & Jensen, M.H. Statistics of co-occurring keywords in confined text messages on Twitter. Eur. Phys. J. Spec. Top. 223, 1849–1858 (2014). https://doi.org/10.1140/epjst/e2014-02230-y

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1140/epjst/e2014-02230-y

Keywords

Search

Navigation