Table of Contents Author Guidelines Submit a Manuscript
Complexity
Volume 2018 (2018), Article ID 9684749, 23 pages
https://doi.org/10.1155/2018/9684749
Research Article

Bipartisanship Breakdown, Functional Networks, and Forensic Analysis in Spanish 2015 and 2016 National Elections

1Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, MA 02115, USA
2Instituto de Fisica Interdisciplinar y Sistemas Complejos (IFISC), CSIC-UIB, Mallorca, Spain
3School of Mathematical Sciences, Queen Mary University of London, Mile End Road, London E14NS, UK

Correspondence should be addressed to Lucas Lacasa

Received 24 October 2017; Accepted 4 December 2017; Published 24 January 2018

Academic Editor: Gerard Olivar-Tost

Copyright © 2018 Juan Fernández-Gracia and Lucas Lacasa. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. R. M. Alvarez, T. E. Hall, and S. D. Hyde, Election Fraud: Detecting and Deterring Electoral Manipulation, Brookings Institution Press, Washington, Wash, USA, 2008.
  2. http://www.infoelectoral.interior.es/min/.
  3. M. J. Nigrini, Benford’s Law: Applications for Forensic Accounting, Auditing, and Fraud Detection, John Wiley and Sons, New Jersey, NY, USA, 2012.
  4. W. R. Mebane, Election Forensics: Vote Counts and Benford’s Law, Political Method ology Society, University of California, California, Calif, usa, 2006.
  5. P. Klimek, Y. Yegorov, R. Hanel, and S. Thurner, “Statistical detection of systematic election irregularities,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 109, no. 41, pp. 16469–16473, 2012. View at Publisher · View at Google Scholar
  6. M. O. Hill, “Diversity and evenness: a unifying notation and its consequences,” Ecology, vol. 54, no. 2, pp. 427–432, 1973. View at Publisher · View at Google Scholar
  7. V. Latora, V. Nicosia, and G. Russo, Complex Networks: Principles, Methods, and Applications, Cambridge University Press, Cambridge, UK, 2017.
  8. M. Rosvall and C. T. Bergstrom, “Maps of random walks on complex networks reveal community structure,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 105, no. 4, pp. 1118–1123, 2008. View at Publisher · View at Google Scholar · View at Scopus
  9. D. Edler and M. Rosvall, “The MapEquation software package,” http://www.mapequation.org.
  10. F. Benford, “The law of anomalous numbers,” Proceedings of the American Philosophical Society, vol. 78, pp. 551–572, 1938. View at Google Scholar
  11. T. P. Hill, “A statistical derivation of the significant-digit law,” Statistical Science, vol. 10, no. 4, pp. 354–363, 1995. View at Publisher · View at Google Scholar · View at Scopus
  12. B. Luque and L. Lacasa, “The first-digit frequencies of prime numbers and Riemann zeta zeros,” Proceedings of the Royal Society A Mathematical, Physical and Engineering Sciences, vol. 465, no. 2107, pp. 2197–2216, 2009. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  13. R. Mansilla, “Analisis de los resultados electorales a partir de la ley de Benford,” http://www.fisica.unam.mx/octavio.
  14. B. F. Roukema, Benford’s Law Anomalies in the 2009 Iranian Election, Torun Centre for Astronomy: Nicolaus Copernicus University, Torun, Poland, 2009. View at Publisher · View at Google Scholar
  15. T. P. Hill, “The significant-digit phenomenon,” The American Mathematical Monthly, vol. 102, no. 4, pp. 322–327, 1995. View at Publisher · View at Google Scholar · View at MathSciNet
  16. C. Breunig and A. Goerres, “Searching for electoral irregularities in an established democracy: applying Benford's Law tests to Bundestag elections in Unified Germany,” Electoral Studies, vol. 30, no. 3, pp. 534–545, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. D. Kobak, S. Shpilkin, and M. S. Pshenichnikov, “Statistical fingerprints of electoral fraud?” Significance, vol. 13, no. 4, pp. 20–23, 2016. View at Publisher · View at Google Scholar · View at Scopus
  18. D. Kobak, S. Shpilkin, and M. S. Pshenichnikov, “Integer percentages as electoral falsification fingerprints,” The Annals of Applied Statistics, vol. 10, no. 1, pp. 54–73, 2016. View at Publisher · View at Google Scholar · View at MathSciNet
  19. J. Deckert, M. Myagkov, and P. C. Ordeshook, “Benford's Law and the detection of election fraud,” Political Analysis, vol. 19, no. 3, pp. 245–268, 2011. View at Publisher · View at Google Scholar · View at Scopus
  20. W. R. Mebane, “Comment on “benford's law and the detection of election fraud”,” Political Analysis, vol. 19, no. 3, pp. 269–272, 2011. View at Publisher · View at Google Scholar · View at Scopus