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Uncovering Randomness and Success in Society

Author

Listed:
  • Sarika Jalan
  • Camellia Sarkar
  • Anagha Madhusudanan
  • Sanjiv Kumar Dwivedi

Abstract

An understanding of how individuals shape and impact the evolution of society is vastly limited due to the unavailability of large-scale reliable datasets that can simultaneously capture information regarding individual movements and social interactions. We believe that the popular Indian film industry, “Bollywood”, can provide a social network apt for such a study. Bollywood provides massive amounts of real, unbiased data that spans more than 100 years, and hence this network has been used as a model for the present paper. The nodes which maintain a moderate degree or widely cooperate with the other nodes of the network tend to be more fit (measured as the success of the node in the industry) in comparison to the other nodes. The analysis carried forth in the current work, using a conjoined framework of complex network theory and random matrix theory, aims to quantify the elements that determine the fitness of an individual node and the factors that contribute to the robustness of a network. The authors of this paper believe that the method of study used in the current paper can be extended to study various other industries and organizations.

Suggested Citation

  • Sarika Jalan & Camellia Sarkar & Anagha Madhusudanan & Sanjiv Kumar Dwivedi, 2014. "Uncovering Randomness and Success in Society," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-8, February.
    • Handle: RePEc:plo:pone00:0088249
    DOI: 10.1371/journal.pone.0088249
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    References listed on IDEAS

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    1. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    2. Watts, Alison, 2001. "A Dynamic Model of Network Formation," Games and Economic Behavior, Elsevier, vol. 34(2), pages 331-341, February.
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    1. Matharoo, Gurpreet S. & Hashmi, Javeria A., 2020. "Spontaneous back-pain alters randomness in functional connections in large scale brain networks: A random matrix perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).

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