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The Rippling Effect of Social Influence via Phone Communication Network

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Complex Spreading Phenomena in Social Systems

Part of the book series: Computational Social Sciences ((CSS))

Abstract

Phenomena such as “small-world” and “six degrees of separation” reveal the connectivity between individuals that are seemingly unrelated in the society. Beyond merely connectivity, it has been shown in recent years that social contagion exists in online interactions. Along this line of investigation, we are interested in the subtle and invisible social influence on real-world behavior across offline communication networks. In particular, we study how social influence propagates and triggers behavioral change, and how such effect expands deeply across the social network in a way similar to the physical phenomenon of ripples across the water. To this end, we analyze a large-scale one-month international event in Andorra using nation-wide mobile phone data, and investigate the change in the likelihood of attending the event for people that have been influenced by and are of different social distances from the attendees. Our results suggest that social influence exhibits the ripple effect, decaying across social distances from the source but persisting up to six degrees of separation in the social network. We further show that such influence decays as communication delay increases and communication intensity decreases, and that it is stronger among people who are more explorative geographically. Our findings may have important implications in a number of domains, such as marketing, public health, and social mobilizations.

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Notes

  1. 1.

    Unobserved confounding variables are difficult to control for by using matching-based methods. To partly address the issue that tourists may travel together and social links may not pass social influence, we remove individual pairs who are potentially on the same trip to Andorra. This can be inferred based on whether individuals stay at the same hotel at the same night.

References

  1. Anagnostopoulos A, Kumar R, Mahdian M (2008) Influence and correlation in social networks. In: 14th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, New York, pp 7–15

    Google Scholar 

  2. Aral S (2011) Commentary-identifying social influence: a comment on opinion leadership and social contagion in new product diffusion. Mark Sci 30(2):217–223

    Article  MathSciNet  Google Scholar 

  3. Aral S (2012) Social science: poked to vote. Nature 489(7415):212–214

    Article  ADS  Google Scholar 

  4. Aral S, Muchnik L, Sundararajan A (2009) Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. Proc Natl Acad Sci 106(51):21544–21549

    Article  ADS  Google Scholar 

  5. Backstrom L, Boldi P, Rosa M, Ugander J, Vigna S (2012) Four degrees of separation in Proceedings of the 4th annual ACM web science conference. ACM, New York, pp 33–42

    Google Scholar 

  6. Bond RM et al (2012) A 61-million-person experiment in social influence and political mobilization. Nature 489(7415):295–298.

    Article  ADS  Google Scholar 

  7. Christakis N, Fowler J (2009) Connected: the surprising power of our social networks and how they shape our lives. Little Brown and Company, New York

    Google Scholar 

  8. Deville P et al (2016) Scaling identity connects human mobility and social interactions. Proc Natl Acad Sci 113(26):201525443

    Article  Google Scholar 

  9. Gleeson JP, Cellai D, Onnela JP, Porter MA, Reed-Tsochas F (2014) A simple generative model of collective online behavior. Proc Natl Acad Sci 111(29):10411–10415

    Article  ADS  Google Scholar 

  10. Hill S, Provost F, Volinsky C (2006) Network-based marketing: Identifying likely adopters via consumer networks. Stat Sci 21(2):256–276

    Article  MathSciNet  MATH  Google Scholar 

  11. King G, Nielsen R (2016) Why propensity scores should not be used for matching

    Google Scholar 

  12. Leng Y, Rudolph L, Pentland A, Zhao J, Koutsopolous HN (2016) Managing travel demand: location recommendation for system efficiency based on mobile phone data. CoRR abs/1610.06825

    Google Scholar 

  13. Lobel I, Sadler E (2015) Preferences, homophily, and social learning. Oper Res 64(3):564–584

    Article  MathSciNet  MATH  Google Scholar 

  14. Milgram S (1967) The small world problem. Psychol Today 1(1):61–67

    Google Scholar 

  15. Miritello G, Moro E, Lara R (2011) Dynamical strength of social ties in information spreading. Phys Rev E 83(4):045102

    Article  ADS  Google Scholar 

  16. Normand SLT et al (2001) Validating recommendations for coronary angiography following acute myocardial infarction in the elderly: a matched analysis using propensity scores. J Clin Epidemiol 54(4):387–398

    Article  Google Scholar 

  17. Onnela JP et al (2007) Structure and tie strengths in mobile communication networks. Proc Natl Acad Sci 104(18):7332–7336

    Article  ADS  Google Scholar 

  18. Pickard G et al (2011) Time-critical social mobilization. Science 334:509–512

    Article  ADS  Google Scholar 

  19. Rutherford A et al (2013) Limits of social mobilization. Proc Natl Acad Sci 110(16): 6281–6286

    Article  ADS  Google Scholar 

  20. Stuart EA (2010) Matching methods for causal inference: a review and a look forward. Stat Sci Rev J Inst Math Stat 25(1):1

    MathSciNet  MATH  Google Scholar 

  21. Toole JL, Herrera-Yaqüe C, Schneider CM, González MC (2015) Coupling human mobility and social ties. J R Soc Interface 12(105):20141128

    Article  Google Scholar 

  22. Toulis P, Kao EK (2013) Estimation of causal peer influence effects. ICML 28(3):1489–1497

    Google Scholar 

  23. Ugander J, Backstrom L, Marlow C, Kleinberg J (2012) Structural diversity in social contagion. Proc Natl Acad Sci 109(16):5962–5966

    Article  ADS  Google Scholar 

  24. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(6684):440–442

    Article  ADS  MATH  Google Scholar 

  25. VanderWeele TJ (2013) Inference for influence over multiple degrees of separation on a social network. Stat Med 32(4):591–596

    Article  MathSciNet  Google Scholar 

  26. Zhao J, Wu J, Xu K (2010) Weak ties: Subtle role of information diffusion in online social networks. Phys Rev E 82(1):016105

    Article  ADS  Google Scholar 

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Correspondence to Alex ‘Sandy’ Pentland .

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Leng, Y., Dong, X., Moro, E., Pentland, A.‘. (2018). The Rippling Effect of Social Influence via Phone Communication Network. In: Lehmann, S., Ahn, YY. (eds) Complex Spreading Phenomena in Social Systems. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-77332-2_17

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