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Social Neointeraction on Facebook, Presidential Campaign Mexico 2018

  • Carlos Augusto Jiménez Zarate
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)

Abstract

In 2008, there was a turning point in the history of electoral campaigns, the first presidential campaign of Barack Obama was the beginning of policy 2.0. Obama’s campaign team demonstrated the power and influence in modern society, of the social-digital networks and diverse platforms such as Google, YouTube, Twitter, instant messaging and websites, included in what is called information technologies and communication (ICT). Ten years after that mythical election, a new paradigm becomes more evident. They are the 4.0 networks which will interconnect almost everything to the internet, within this new dynamic, the social networks are also evolving, today it is not just about uploading or viewing content, but to interact and thereby generate broadcast networks. Within the spectrum of social media, there is one that has become, in the cornerstone of modern communication. Facebook is the most important social network at international level, its evolution has been vertiginous, and it went from being a network among friends, to become an indispensable advertising platform in the world of digital marketing, to such a degree that it has positioned itself as the second medium, recipient of advertising spending, just below Google. Facebook is a multiplatform, where you can find applications, games and pages known as “fanpages”, these websites represent, for companies, political parties, public figures and for governmental and civil organizations, a virtual system of social interaction. When users comment on a publication, discussion or debate networks can be generated among users, increasing the organic scope of the publication. The present investigation will focus on analyzing the structure of the networks that generate the likes in the comments made, within the fanpages of the presidential candidates in Mexico, who have positioned themselves as leaders in most of the electoral polls, for the presidency from Mexico. The set of data and information obtained as: degree of interactions, reactions, discussion, debate, support, comments and responses, can be called “neo social interaction”. This result will serve to have an alternative vision, about the popularity, from the point of view of the interactions in their fanpages, taking into account that Facebook has positioned itself as the most influential medium for obtaining political and electoral information.

Keywords

Social network analysis Social neointeraction Viral reaction Viral sentiment Networks on Facebook 

References

  1. 1.
    Barabási, A.: From network structure. IEEE Control Systems Magazine, 33–42, August 2007.  https://doi.org/10.1109/MCS.2007.384127
  2. 2.
    Newman, M.E.J.: The structure and function of complex networks. Siam Rev. 45(2), 167–256 (2002).  https://doi.org/10.1137/S003614450342480ADSMathSciNetCrossRefMATHGoogle Scholar
  3. 3.
    Anderson, A., Huttenlocher, D., Kleinberg, J., Leskovec, J., Tiwari, M.: Global diffusion via cascading invitations: structure, growth, and homophily. In: Proceedings of the 24th International Conference on World Wide Web (WWW 2015), pp. 66–76 (2015).  https://doi.org/10.1145/2736277.2741672
  4. 4.
    Bond, R.M., Fariss, C.J., Jones, J., Kramer, A.D.I., Marlow, C., Settle, J.E., Fowler, J.H.: A 61-million-person experiment in social influence and political mobilization. Nature 489(7415), 295–298 (2012).  https://doi.org/10.1038/nature11421ADSCrossRefGoogle Scholar
  5. 5.
    Postigo, M.: Campaña en la red: estrategias de marketing electoral en Internet. Revista Académica de Marketing (2012). http://dialnet.unirioja.es/servlet/articulo?codigo=4125640&info=resumen&idioma=SPA
  6. 6.
    Jiménez Zarate, C.A.: Dinámica y efectividad de las fanpages de Facebook de candidatos a gobernador en los resultados electorales. Innovaciones de Negocios, 13(26), 221–238 (2016). http://www.web.facpya.uanl.mx/rev_in/Revistas/13_26/13.26 A4.pdf
  7. 7.
    Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.: Complex networks: Structure and dynamics, 424, 175–308 (2006).  https://doi.org/10.1016/j.physrep.2005.10.009
  8. 8.
    Braha, D., De Aguiar, M.A.M.: Voting contagion: Modeling and analysis of a century of U.S. presidential elections. PLoS One 12(5), 1–30 (2017).  https://doi.org/10.1371/journal.pone.0177970CrossRefGoogle Scholar
  9. 9.
    Slattery, R.E., McHardy, R.R., Bairathi, R.: On the Topology of the Facebook Page Network, 3 (2013). http://arxiv.org/abs/1307.2189
  10. 10.
    McSweeney, P.: Gephi Network Statistics. Google Summer of Code, 1–8. (2009). http://gephi.org/google-soc/gephi-netalgo.pdf
  11. 11.
    Freeman, L.C.: A Set of Measures of Centrality Based on Betweenness. Sociometry.  https://doi.org/10.2307/3033543
  12. 12.
    Bonacich, P.: Power and centrality: a family of measures. Am. J. Sociol. 92(5), 1170–1182 (1987).  https://doi.org/10.1086/228631. Accessed 1977CrossRefGoogle Scholar
  13. 13.
    Goel, S., Anderson, A., Hofman, J., Watts, D.J.: The Structural Virality of Online Diffusion. Manag. Sci. 62(1), 150722112809007 (2015).  https://doi.org/10.1287/mnsc.2015.2158CrossRefGoogle Scholar
  14. 14.

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Faculty of Administration and Public Accounting of the Autonomous University of Nuevo Leon (FACPYA-UANL)University City, San Nicolás de los GarzaMéxico

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