Network Topology and Tie Strength in Online Communities of Practice

  • Ecem BasakEmail author
  • Ali Tafti
  • Peng Huang
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 813)


Due to the heterogeneities in the nature of complex networks, it is possible that the relationship between tie strength and network topology does not follow a universal rule. Since networks are shaped by different mechanisms, the correlation of the network topology and tie strengths can either constrain or facilitate the information flow in the networks, and the global role of strong and weak ties can differ from network to network. The theory of strength of weak ties and the global efficiency principle offer two alternative lenses in explaining tie strength and network topology. We aim at investigating these two contrasting theories by exploring the relationship between tie strength and net-work topology in online communities of practice. Our research context is the online community platform created by SAP, the largest enterprise software vendor. We use two-way fixed-effects panel data models to examine the relationship between tie strength and network topology, and the results provide support for the strength of weak ties theory.


The theory of strength of weak ties The global efficiency principle Tie strength Network topology 


  1. 1.
    Grabowicz, P.A., Ramasco, J.J., Moro, E., Pujol, J.M., Eguiluz, V.M.: Social features of online networks: The strength of intermediary ties in online social media. PLoS One 7(1) (2012)Google Scholar
  2. 2.
    Granovetter, M.S.: The strength of weak ties. Am. J. Sociol. 78(6), 1360–1380 (1973)CrossRefGoogle Scholar
  3. 3.
    Onnela, J.P., Saramäki, J., Hyvönen, J., Szabó, G., Lazer, D., Kaski, K., Kertész, J., Barabási, A.L.: Structure and tie strengths in mobile communication networks. PNAS 104(18), 7332–7336 (2007)CrossRefGoogle Scholar
  4. 4.
    Burt, R.S.: Structural holes versus network closure as social capital. In: Social Capital: Theory and Research, pp. 31–56 (2000)Google Scholar
  5. 5.
    Aral, S., Van Alstyne, M.: The diversity-bandwith trade-off. Am. J. Sociol. 117(1), 90–171 (2011)CrossRefGoogle Scholar
  6. 6.
    Barrat, A., Barthélemy, M., Pastor-Satorras, R., Vespignani, A.: The architecture of complex weighted networks. PNAS 101(11), 3747–3751 (2004)CrossRefGoogle Scholar
  7. 7.
    Toroczkai, Z., Bassler, K.E.: Network dynamics: Jamming is limited in scale-free systems. Nature 428(6984), 716 (2004)CrossRefGoogle Scholar
  8. 8.
    Huang, P., Tafti, A.R., Mithas, S.: Platform sponsor’s investments and user contributions in knowledge communities: The role of knowledge seeding. MIS Q. 42(1), 213–240 (2018)CrossRefGoogle Scholar
  9. 9.
    Pappalardo, L., Rossetti, G., Pedreschi, D.: How well do we know each other? Detecting tie strength in multidimensional social networks. Social Networks Analysis and Mining (ASONAM), pp. 1040–1045. IEEE, New York (2012)Google Scholar
  10. 10.
    Noka, E., Hoxha, F.: Comparative analysis of the structural and weighted properties in Albanian social networks. J. Multidiscip. Eng. Sci. Technol. 3(4), 4505–4509 (2016)Google Scholar
  11. 11.
    Pan, R.K., Saramäki, J.: The strength of strong ties in scientific collaboration networks. EPL (Europhys. Lett.) 97(1), 18007 (2012)CrossRefGoogle Scholar
  12. 12.
    Hamilton, D., Odetunde, O., Young, K.: Investigating conversation connectivity in politically- and socially-charged Twitter discussions (2014)Google Scholar
  13. 13.
    Latora, V., Marchiori, M.: Efficient behavior of small-world networks. Phys. Rev. Lett. 87(19), 198701 (2001)CrossRefGoogle Scholar
  14. 14.
    Goh, K.I., Kahng, B., Kim, D.: Universal behavior of load distribution in scale-free networks. Phys. Rev. Lett. 87(27), 278701 (2001)CrossRefGoogle Scholar
  15. 15.
    Colizza, V., Barrat, A., Barthelemy, M., Vespignani, A.: The role of the airline transportation network in the prediction and predictability of global epidemics. PNAS 103(7), 2015–2020 (2006)CrossRefGoogle Scholar
  16. 16.
    Van der Leij, M., Goyal, S.: Strong ties in a small world. Review of Network Economics 10(2), (2011)Google Scholar
  17. 17.
    Borgatti, S.P., Everett, M.G.: Models of core/periphery structures. Soc. Netw. 21(4), 375–395 (2000)CrossRefGoogle Scholar
  18. 18.
    Girvan, M., Newman, M.E.J.: Community structure in social and biological networks. PNAS 99(12), 7821–7826 (2002)MathSciNetCrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of Business AdministrationUniversity of Illinois at ChicagoChicagoUSA
  2. 2.Robert H. Smith School of BusinessUniversity of MarylandCollege ParkUSA

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