Networking strategies and efficiency in human communication networks

Kyosuke Tanaka, Emoke-Agnes Horvat

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationComplex Networks and Their Applications VII - Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018
EditorsLuca Maria Aiello, Hocine Cherifi, Pietro Lió, Luis M. Rocha, Chantal Cherifi, Renaud Lambiotte
PublisherSpringer Verlag
Pages258-270
Number of pages13
ISBN (Print)9783030054137
DOIs
StatePublished - Jan 1 2019
Event7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018 - Cambridge, United Kingdom
Duration: Dec 11 2018Dec 13 2018

Publication series

NameStudies in Computational Intelligence
Volume813
ISSN (Print)1860-949X

Other

Other7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018
CountryUnited Kingdom
CityCambridge
Period12/11/1812/13/18

Fingerprint

Telecommunication networks
Information theory
Heterogeneous networks
Communication
Computer simulation

Keywords

  • Efficiency
  • Human communication network
  • Networking strategies
  • Reciprocity
  • Simulations
  • Triadic Closure

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Tanaka, K., & Horvat, E-A. (2019). Networking strategies and efficiency in human communication networks. In L. M. Aiello, H. Cherifi, P. Lió, L. M. Rocha, C. Cherifi, & R. Lambiotte (Eds.), Complex Networks and Their Applications VII - Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018 (pp. 258-270). (Studies in Computational Intelligence; Vol. 813). Springer Verlag. https://doi.org/10.1007/978-3-030-05414-4_21
Tanaka, Kyosuke ; Horvat, Emoke-Agnes. / Networking strategies and efficiency in human communication networks. Complex Networks and Their Applications VII - Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018. editor / Luca Maria Aiello ; Hocine Cherifi ; Pietro Lió ; Luis M. Rocha ; Chantal Cherifi ; Renaud Lambiotte. Springer Verlag, 2019. pp. 258-270 (Studies in Computational Intelligence).
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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.",
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Tanaka, K & Horvat, E-A 2019, Networking strategies and efficiency in human communication networks. in LM Aiello, H Cherifi, P Lió, LM Rocha, C Cherifi & R Lambiotte (eds), Complex Networks and Their Applications VII - Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018. Studies in Computational Intelligence, vol. 813, Springer Verlag, pp. 258-270, 7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018, Cambridge, United Kingdom, 12/11/18. https://doi.org/10.1007/978-3-030-05414-4_21

Networking strategies and efficiency in human communication networks. / Tanaka, Kyosuke; Horvat, Emoke-Agnes.

Complex Networks and Their Applications VII - Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018. ed. / Luca Maria Aiello; Hocine Cherifi; Pietro Lió; Luis M. Rocha; Chantal Cherifi; Renaud Lambiotte. Springer Verlag, 2019. p. 258-270 (Studies in Computational Intelligence; Vol. 813).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - 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.

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Tanaka K, Horvat E-A. Networking strategies and efficiency in human communication networks. In Aiello LM, Cherifi H, Lió P, Rocha LM, Cherifi C, Lambiotte R, editors, Complex Networks and Their Applications VII - Volume 2 Proceedings The 7th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2018. Springer Verlag. 2019. p. 258-270. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-030-05414-4_21