Skip to main content
Log in

A data analysis of political polarization using random matrix theory

  • Letter
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

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

Access this article

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

Instant access to the full article PDF.

References

  1. Bello-Orgaz G, Jung J J, Camacho D. Social big data: recent achievements and new challenges. Inf Fusion, 2016, 28: 45–59

    Article  Google Scholar 

  2. Cui Q, Gong Z, Ni W, et al. Stochastic online learning for mobile edge computing: learning from changes. IEEE Commun Mag, 2019, 57: 63–69

    Article  Google Scholar 

  3. Couillet R, Debbah M. Random Matrix Methods for Wireless Communications. Cambridge: Cambridge University Press, 2011

    Book  MATH  Google Scholar 

  4. Bai Z, Silverstein J W. Spectral Analysis of Large Dimensional Random Matrices. New York: Springer, 2010

    Book  MATH  Google Scholar 

  5. Yang Y, Shen F, Huang Z, et al. Discrete nonnegative spectral clustering. IEEE Trans Knowl Data Eng, 2017, 29: 1834–1845

    Article  Google Scholar 

  6. Michael D, Carroll, D, Jocelyn K, et al. Political polarization in the American public. Pew Research Center, 2014. http://www.people-press.org/2014/06/12/political-polarization-in-the-american-public/

  7. Vallet P, Loubaton P, Mestre X. Improved subspace estimation for multivariate observations of high dimension: the deterministic signals case. IEEE Trans Inform Theor, 2012, 58: 1043–1068

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

This work was supported in part by National Science Fund for Distinguished Young Scholars (Grant No. 61325006), in part by National Nature Science Foundation of China (Grant No. 61631005), in part by Beijing Municipal Science and Technology Project (Grant No. Z181100003218005), and in part by 111 Project of China (Grant No. B16006).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaofeng Tao.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, H., Tao, X., Li, N. et al. A data analysis of political polarization using random matrix theory. Sci. China Inf. Sci. 63, 129303 (2020). https://doi.org/10.1007/s11432-019-9841-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11432-019-9841-4

Navigation