skip to main content
10.1145/3110025.3110027acmconferencesArticle/Chapter ViewAbstractPublication PageskddConference Proceedingsconference-collections
short-paper
Public Access

Which friends are more popular than you?: Contact strength and the friendship paradox in social networks

Authors Info & Claims
Published:31 July 2017Publication History

ABSTRACT

The friendship paradox states that in a social network, egos tend to have lower degree than their alters, or, "your friends have more friends than you do". Most research has focused on the friendship paradox and its implications for information transmission, but treating the network as static and unweighted. Yet, people can dedicate only a finite fraction of their attention budget to each social interaction: a high-degree individual may have less time to dedicate to individual social links, forcing them to modulate the quantities of contact made to their different social ties. Here we study the friendship paradox in the context of differing contact volumes between egos and alters, finding a connection between contact volume and the strength of the friendship paradox. The most frequently contacted alters exhibit a less pronounced friendship paradox compared with the ego, whereas less-frequently contacted alters are more likely to be high degree and give rise to the paradox. We argue therefore for a more nuanced version of the friendship paradox: "your closest friends have slightly more friends than you do", and in certain networks even: "your best friend has no more friends than you do". We demonstrate that this relationship is robust, holding in both a social media and a mobile phone dataset. These results have implications for information transfer and influence in social networks, which we explore using a simple dynamical model.

References

  1. S. L. Feld, "Why your friends have more friends than you do," American Journal of Sociology, pp. 1464--1477, 1991. Google ScholarGoogle ScholarCross RefCross Ref
  2. S. L. Feld and B. Grofman, "Variation in class size, the class size paradox, and some consequences for students," Research in Higher Education, vol. 6, no. 3, pp. 215--222, 1977. Google ScholarGoogle ScholarCross RefCross Ref
  3. D. Hemenway, "Why your classes are larger than "average"," Mathematics Magazine, vol. 55, no. 3, pp. 162--164, 1982. Google ScholarGoogle ScholarCross RefCross Ref
  4. M. Granovetter, "The Strength of Weak Ties," The American Journal of Sociology, vol. 78, no. 6, pp. 1360--1380, 1973. Google ScholarGoogle ScholarCross RefCross Ref
  5. R. I. Dunbar, "Coevolution of neocortical size, group size and language in humans," Behav. brain sci., vol. 16, no. 04, pp. 681--694, 1993. Google ScholarGoogle ScholarCross RefCross Ref
  6. H. Kwak, C. Lee, H. Park, and S. Moon, "What is Twitter, a social network or a news media?" in Proceedings of the 19th international conference on World wide web. ACM, 2010, pp. 591--600. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. N. O. Hodas, F. Kooti, and K. Lerman, "Friendship paradox redux: Your friends are more interesting than you," in Proc. 7th International AAAI Conference On Weblogs And Social Media (ICWSM), 2013.Google ScholarGoogle Scholar
  8. N. B. Ellison, C. Steinfield, and C. Lampe, "The benefits of Facebook friends: social capital and college students use of online social network sites," Journal of Computer-Mediated Communication, vol. 12, no. 4, pp. 1143--1168, 2007. Google ScholarGoogle ScholarCross RefCross Ref
  9. J. Ugander, B. Karrer, L. Backstrom, and C. Marlow, "The anatomy of the Facebook social graph," arXiv preprint arXiv:1111.4503, 2011.Google ScholarGoogle Scholar
  10. J.-P. Onnela, J. Saramäki, J. Hyvönen, G. Szabó, D. Lazer, K. Kaski, J. Kertész, and A.-L. Barabási, "Structure and tie strengths in mobile communication networks," Proceedings of the National Academy of Sciences, vol. 104, no. 18, p. 7332, 2007. Google ScholarGoogle ScholarCross RefCross Ref
  11. J. P. Bagrow, D. Wang, and A.-L. Barabási, "Collective response of human populations to large-scale emergencies," PLoS ONE, vol. 6, no. 3, p. e17680, 2011. Google ScholarGoogle Scholar
  12. L. Gao, C. Song, Z. Gao, A.-L. Barabási, J. P. Bagrow, and D. Wang, "Quantifying information flow during emergencies," Scientific Reports, vol. 4, p. 3997, 2014. Google ScholarGoogle ScholarCross RefCross Ref
  13. T. V. Pollet, S. G. Roberts, and R. I. Dunbar, "Extraverts have larger social network layers," Journal of Individual Differences, 2011. Google ScholarGoogle ScholarCross RefCross Ref
  14. E. W. Zuckerman and J. T. Jost, "What makes you think you're so popular? Self-evaluation maintenance and the subjective side of the" friendship paradox"," Social Psychology Quarterly, pp. 207--223, 2001. Google ScholarGoogle ScholarCross RefCross Ref
  15. N. O. Hodas and K. Lerman, "How visibility and divided attention constrain social contagion," in Privacy, Security, Risk and Trust (PASSAT), 2012 International Conference on and 2012 International Confernece on Social Computing (SocialCom). IEEE, 2012, pp. 249--257. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. M. C. Gonzalez, C. A. Hidalgo, and A.-L. Barabasi, "Understanding individual human mobility patterns," Nature, vol. 453, no. 7196, pp. 779--782, 2008. Google ScholarGoogle ScholarCross RefCross Ref
  17. C. Song, Z. Qu, N. Blumm, and A.-L. Barabási, "Limits of predictability in human mobility," Science, vol. 327, no. 5968, pp. 1018--1021, 2010. Google ScholarGoogle ScholarCross RefCross Ref
  18. J. P. Bagrow and Y.-R. Lin, "Mesoscopic structure and social aspects of human mobility," PloS one, vol. 7, no. 5, p. e37676, 2012. Google ScholarGoogle ScholarCross RefCross Ref
  19. G. K. Zipf, Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology. Addison-Wesley, 1949.Google ScholarGoogle Scholar
  20. M. R. Frank, L. Mitchell, P. S. Dodds, and C. M. Danforth, "Happiness and the patterns of life: A study of geolocated tweets," Scientific Reports, vol. 3, no. 2625, 2013. Google ScholarGoogle ScholarCross RefCross Ref
  21. M. Molloy and B. Reed, "A critical point for random graphs with a given degree sequence," Random structures & algorithms, vol. 6, no. 2--3, pp. 161--180, 1995.Google ScholarGoogle Scholar
  22. M. Molloy and B. Reed, "The size of the giant component of a random graph with a given degree sequence," Combinatorics, probability and computing, vol. 7, no. 03, pp. 295--305, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. D. A. Schult and P. Swart, "Exploring network structure, dynamics, and function using NetworkX," in Proceedings of the 7th Python in Science Conferences (SciPy 2008), vol. 2008, 2008, pp. 11--16.Google ScholarGoogle Scholar
  24. R. M. Anderson and R. M. May, Infectious diseases of humans: dynamics and control. Wiley Online Library, 1992, vol. 28.Google ScholarGoogle Scholar
  25. M. E. J. Newman, Networks: An introduction. Oxford: Oxford University Press, 2010. Google ScholarGoogle ScholarCross RefCross Ref
  26. Y.-H. Eom and H.-H. Jo, "Generalized friendship paradox in complex networks: The case of scientific collaboration," Scientific Reports, vol. 4, p. 4603, 2014. Google ScholarGoogle ScholarCross RefCross Ref
  27. N. A. Christakis and J. H. Fowler, "Social network sensors for early detection of contagious outbreaks," PLOS ONE, vol. 5, no. 9, pp. 1--8, 09 2010.Google ScholarGoogle ScholarCross RefCross Ref
  28. M. Garcia-Herranz, E. Moro, M. Cebrian, N. A. Christakis, and J. H. Fowler, "Using friends as sensors to detect global-scale contagious outbreaks," PLOS ONE, vol. 9, no. 4, pp. 1--7, 04 2014.Google ScholarGoogle ScholarCross RefCross Ref
  29. M. Karsai, M. Kivelä, R. Pan, K. Kaski, J. Kertész, A.-L. Barabási, and J. Saramäki, "Small but slow world: How network topology and burstiness slow down spreading," Physical Review E, vol. 83, no. 2, p. 025102, 2011. Google ScholarGoogle ScholarCross RefCross Ref
  30. D. Mocanu, L. Rossi, Q. Zhang, M. Karsai, and W. Quattrociocchi, "Collective attention in the age of (mis)information," Computers in Human Behavior, vol. 51, pp. 1198--1204, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. J. Borge-Holthoefer, N. Perra, B. Gonçalves, S. González-Bailón, A. Arenas, Y. Moreno, and A. Vespignani, "The dynamics of information-driven coordination phenomena: A transfer entropy analysis," Science Advances, vol. 2, no. 4, 2016. Google ScholarGoogle ScholarCross RefCross Ref
  32. M. Karsai, K. Kaski, and J. Kertsz, "Correlated dynamics in egocentric communication networks," PLOS ONE, vol. 7, no. 7, pp. 1--9, 07 2012.Google ScholarGoogle ScholarCross RefCross Ref
  33. R. Cohen, S. Havlin, and D. ben-Avraham, "Efficient immunization strategies for computer networks and populations," Phys. Rev. Lett., vol. 91, p. 247901, Dec 2003.Google ScholarGoogle ScholarCross RefCross Ref
  34. M. Garcia-Herranz, E. Moro, M. Cebrian, N. A. Christakis, and J. H. Fowler, "Using friends as sensors to detect global-scale contagious outbreaks," PLoS ONE, vol. 9, no. 4, p. e92413, 2014. Google ScholarGoogle ScholarCross RefCross Ref
  1. Which friends are more popular than you?: Contact strength and the friendship paradox in social networks

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        ASONAM '17: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017
        July 2017
        698 pages
        ISBN:9781450349932
        DOI:10.1145/3110025

        Copyright © 2017 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 31 July 2017

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • short-paper
        • Research
        • Refereed limited

        Acceptance Rates

        Overall Acceptance Rate116of549submissions,21%

        Upcoming Conference

        KDD '24

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader