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Networking Strategies and Efficiency in Human Communication Networks

  • Kyosuke Tanaka
  • Emőke-Ágnes Horvát
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 813)

Abstract

Individuals communicate with each other strategically to improve their access to information and to capitalize on social connections in attaining personal and professional goals. Yet, we know little about how specific networking strategies impact the efficiency of communication networks both at a global and local level. Here, we perform data-driven computer simulations that examine the effect of two predominant networking strategies: (i) structural change, involving addition and deletion of communication channels and (ii) frequency change, involving increase or decrease of communication on existing channels. In our proposed framework, these two strategies encompass the spectrum of exploring new connections and exploiting existing ones, and are implemented based on the generic social processes of interaction reciprocity and triadic closure. Three main results emerge from our simulations. First, our structural and frequency change strategies designed to reflect human behavior differ from null models represented by random strategies. Second, they have distinct effects on global and local efficiency. Third, these strategies work consistently across heterogeneous network structures and various network evolution scenarios. Taken together, our findings reassess conventional wisdom about the effectiveness of networking strategies and introduce novel frameworks to study the impact of networking via modeling approaches informed by social and communication theory.

Keywords

Networking Strategies Efficiency Reciprocity Triadic Closure Human Communication Network Simulations 

Notes

Acknowledgement

This research was partly supported by the National Science Foundation under Grant No. IIS-1755873. The authors would like to thank Zachary Gibson and Nick Hagar for their comments on an earlier version of the manuscript.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Northwestern UniversityEvanstonUSA

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