Skip to main content
SpringerLink
Log in
SpringerLink
Log in

Complex Contagions: A Decade in Review

  • Chapter
  • First Online:
Complex Spreading Phenomena in Social Systems

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

Abstract

Since the publication of “Complex Contagions and the Weakness of Long Ties” in 2007, complex contagions have been studied across an enormous variety of social domains. In reviewing this decade of research, we discuss recent advancements in applied studies of complex contagions, particularly in the domains of health, innovation diffusion, social media, and politics. We also discuss how these empirical studies have spurred complementary advancements in the theoretical modeling of contagions, which concern the effects of network topology on diffusion, as well as the effects of individual-level attributes and thresholds. In synthesizing these developments, we suggest three main directions for future research. The first concerns the study of how multiple contagions interact within the same network and across networks, in what may be called an ecology of contagions. The second concerns the study of how the structure of thresholds and their behavioral consequences can vary by individual and social context. The third area concerns the roles of diversity and homophily in the dynamics of complex contagion, including both diversity of demographic profiles among local peers and the broader notion of structural diversity within a network. Throughout this discussion, we make an effort to highlight the theoretical and empirical opportunities that lie ahead.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Kramer et al.’s study also raised the important point about the ethics of experimentation on social media. While previous social media studies using experimentally designed social platforms [7, 8, 49, 50] enrolled subjects into their online platform with an explicit process of informed consent, Kramer et al.’s study on Facebook used existing networks of peers without their explicit consent. It is an important topic of ongoing discussion how to properly use existing peer networks, such as Facebook and Twitter, to conduct experiments that manipulate user behavior.

References

  1. Granovetter M (1973) The strength of weak ties. Am J Sociol 78:1360–1380

    Article  Google Scholar 

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

    Article  MATH  ADS  Google Scholar 

  3. Coates TJ, Richter L, Caceres C (2008) Behavioural strategies to reduce HIV transmission: how to make them work better. Lancet 372(9639):669–684

    Article  Google Scholar 

  4. Centola D, Macy M (2007) Complex contagions and the weakness of long ties. Am J Sociol 113(3):702–734

    Article  Google Scholar 

  5. Coleman JS, Katz E, Menzel H (1966) Medical innovation; a diffusion study. Bobbs-Merrill Co, Indianapolis

    Google Scholar 

  6. Davis G, Greve H (1997) Corporate elites and governance changes in the 1980s. Am J Sociol 103(1):1–37

    Article  Google Scholar 

  7. Centola D (2010) The spread of behavior in an online social network experiment. Science 329(5996):1194–1197

    Article  ADS  Google Scholar 

  8. Centola D (2011) An experimental study of homophily in the adoption of health behavior. Science 334(6060):1269–1272

    Article  ADS  Google Scholar 

  9. Centola D, Eguiluz V, Macy M (2007) Cascade dynamics of complex propagation. Phys A 374:449–456

    Article  Google Scholar 

  10. Christakis NA, Fowler JH (2007) The spread of obesity in a large social network over 32 years. N Engl J Med 357(4):370–379

    Article  Google Scholar 

  11. Christakis NA, Fowler JH (2008) The collective dynamics of smoking in a large social network. N Engl J Med 358(21):2249–2258

    Article  Google Scholar 

  12. Kuhlman C, Kumar A, Tuli G (2011) A bi-threshold model of complex contagion and its application to the spread of smoking behavior. AAAI fall symposium: complex adaptive systems

    Google Scholar 

  13. Kuhlman CJ, Kumar VSA, Marathe MV, Ravi SS, Rosenkrantz DJ (2011) Effects of opposition on the diffusion of complex contagions in social networks: an empirical study. In: Salerno J, Yang SJ, Nau D, Chai SK (eds) Social computing, behavioral-cultural modeling and prediction. SBP 2011, Lecture notes in computer science, vol 6589. Springer, Berlin

    Google Scholar 

  14. Myneni S, Fujimoto K, Cobb N, Cohen T (2015) Content-driven analysis of an online community for smoking cessation: integration of qualitative techniques, automated text analysis, and affiliation networks. Am J Public Health 105(6):1206–1212

    Article  Google Scholar 

  15. Centola D, van de Rijt A (2014) Choosing your network: social preferences in an online health community. Soc Sci Med 125:19–31. https://doi.org/10.1016/j.socscimed.2014.05.019

    Article  Google Scholar 

  16. Aral S, Nicolaides C (2017) Exercise contagion in a global social network. Nat Commun 8:14753

    Article  ADS  Google Scholar 

  17. Zhang J, Brackbill D, Yang S, Becker J, Herbert N, Centola D (2016) Support or competition? How online social networks increase physical activity: a randomized controlled trial. Prev Med Rep 4:453–458

    Article  Google Scholar 

  18. Campbell E, Salathe M (2013) Complex social contagion makes networks more vulnerable to disease outbreaks. Sci Rep 3:1905

    Article  ADS  Google Scholar 

  19. Salathe M, Bonhoeffer S (2008) The effect of opinion clustering on disease outbreaks. J R Soc Interface 5(29):1505–1508

    Article  Google Scholar 

  20. Hébert-Dufresne L, Althouse BM (2015) Complex dynamics of synergistic Coinfections on realistically clustered networks. Proc Natl Acad Sci 112(33):10551–10556

    Article  MathSciNet  MATH  ADS  Google Scholar 

  21. Bass F (1969) A new product growth for model consumer durables. Manag Sci 15(5):215–227

    Article  MATH  Google Scholar 

  22. Schelling T (1973) Hockey helmets, concealed weapons, and daylight saving: a study of binary choices with externalities. J Confl Resolut 17(3):381–428

    Article  Google Scholar 

  23. Bandiera O, Rasul I (2006) Social networks and technology adoption in northern Mozambique. Econ J 116(514):869–902

    Article  Google Scholar 

  24. Oster E, Thornton R (2012) Determinants of technology adoption: peer effects in menstrual cup take-up. J Eur Econ Assoc 10(6):1263–1293

    Article  Google Scholar 

  25. Beaman L, Yishay A, Magruder J, Mobarak M (2015) Can network theory-based targeting increase technology adoption? Working paper

    Google Scholar 

  26. Banerjee A, Chandrasekhar AG, Duflo E, Jackson MO (2013) The diffusion of microfinance. Science 341:6144

    Article  Google Scholar 

  27. Karsai M, Iniguez G, Kaski K, Kertesz J (2014) Complex contagion process in spreading of online innovation. J R Soc Interface 11(101):20140694

    Article  Google Scholar 

  28. Ugander J, Backstrom L, Marlow C, Kleinberg J (2012) Structural diversity in social contagion. PNAS 109(16):5962–5966

    Article  ADS  Google Scholar 

  29. Toole J, Meeyoung C, Gonzalez M (2012) Modeling the adoption of innovations in the presence of geographic and media influences. PLoS One 7(1):1–9

    Google Scholar 

  30. Berger J (2013) Contagious: why things catch on. Simon and Schuster, London

    Google Scholar 

  31. Bakshy E, Eckles D, Yan R, Rosenn I (2012) Social influence in social advertising: evidence from field experiments. arXiv

    Google Scholar 

  32. Borge-Holthoefer J, Baños RA, González-Bailón S, Moreno Y (2013) Cascading behaviour in complex soci-technical networks. J Complex Netw 1:3–24. https://doi.org/10.1093/comnet/cnt006

    Article  Google Scholar 

  33. Kooti F, Yang H, Cha M, Gummadi PK, Mason WA (2012) The emergence of conventions in online social networks. ICWSM

    Google Scholar 

  34. Barash V (2011) The dynamics of social contagion. PhD Dissertation, Cornell University

    Google Scholar 

  35. Weng L, Menczer F, Ahn YY (2013) Virality prediction and community structure in social networks. Sci Rep 3:2522

    Article  ADS  Google Scholar 

  36. Harrigan N, Achananuparp P, Lim E (2012) Influentials, novelty, and social contagion: the viral power of average friends, close communities, and old news. Soc Netw 34(4):470–480

    Article  Google Scholar 

  37. Bakshy E, Rosenn I, Marlow C, Adamic L (2012) The role of social networks in information diffusion. In: Proceedings of ACM WWW 2012

    Google Scholar 

  38. Wu S, Tan C, Kleinberg J, Macy M (2011) Does bad news go away faster? In: Fifth international AAAI conference on weblogs and social media, ICWSM. AAAI

    Google Scholar 

  39. Romero DM, Meeder B, Kleinberg J (2011) Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on twitter. In Proceedings of the 20th international conference on world wide web, ACM, pp 695–704

    Google Scholar 

  40. Barash V, Kelly J (2012) Salience vs committment: dynamics of political hashtags in Russian Twitter. Berkman Center for Internet and Society, Research Publication No. 2012–9

    Google Scholar 

  41. Fink C, Schmidt A, Barash V, Cameron C, Macy M (2016) Complex contagions and the diffusion of popular Twitter hashtags in Nigeria. Soc Networks 6(1):1

    Google Scholar 

  42. Bakshy E, Karrer B, Adamic L (2009) Social influence and the diffusion of user-created content. In Proceedings of the 10th ACM conference on electronic commerce, pp 325–334

    Google Scholar 

  43. State B, Adamic L (2015) The diffusion of support in an online social movement: evidence from the adoption of equal-sign profile pictures. In: CSCW’15 proceedings of the 18th ACM conference on computer supported cooperative work and social computing, pp 1741–1750

    Google Scholar 

  44. Gomez-Rodriguez M, Gummadi K, Schölkopf B (2014) Quantifying information overload in social media and its impact on social contagions. In: Proceedings of the eighth international conference on weblogs and social media, pp. 170–179

    Google Scholar 

  45. Hodas NO, Lerman K (2012) How visibility and divided attention constrain social contagion. Privacy, security, risk and trust (PASSAT). In: 2012 international conference on social computing (SocialCom)

    Google Scholar 

  46. Doerr C, Blenn N, Tang S, Miegham P (2012) Are friends overrated? A study for the social news aggregator Digg.com. Comput Commun 35(7):796–809

    Article  Google Scholar 

  47. Centola D (2013) Social media and the science of health behavior. Circulation 127(21):2135–2144

    Article  Google Scholar 

  48. Kramer A, Guillory J, Hancock J (2014) Experimental evidence of massive-scale emotional contagion through social networks. PNAS 111(24):8788–8790

    Article  ADS  Google Scholar 

  49. Centola D, Baronchelli A (2015) The spontaneous emergence of conventions: an experimental study of cultural evolution. PNAS 112(7):1989–1994

    Article  ADS  Google Scholar 

  50. Salganik MJ, Dodds PS, Watts DJ (2006) Experimental study of inequality and unpredictability in an artificial cultural market. Science 311(5762):854–856

    Article  ADS  Google Scholar 

  51. Krafft P, Macy M, Pentland A (2016) Bots as virtual confederates: design and ethics. The 20th ACM conference on computer-supported cooperative work and social computing (CSCW)

    Google Scholar 

  52. Mønsted B, Sapieżyński P, Ferrara E, Lehmann S (2017) Evidence of complex contagion of information in social media: an experiment using Twitter bots. PLoS One 12(9):e0184148. https://doi.org/10.1371/journal.pone.0184148

    Article  Google Scholar 

  53. Granovetter M (1978) Threshold models of collective behavior. Am J Sociol 83:1420–1443

    Article  Google Scholar 

  54. Centola D (2013) Homophily, networks, and critical mass: solving the start-up problem in large group collective action. Ration Soc 25(1):3–40

    Article  MathSciNet  Google Scholar 

  55. Hassanpour N (2017) A quasi-experimental study of contagion and coordination in urban conflict: evidence from the Syrian civil war in damascus. Unpublished manuscript

    Google Scholar 

  56. González-Bailón S, Borge-Holthoefer J, Rivero A, Moreno Y (2011) The dynamics of protest recruitment through an online network. Sci Rep 1:197. https://www.nature.com/articles/srep00197

    Article  ADS  Google Scholar 

  57. Steinhert-Threlkeld Z (2017) Spontaneous collective action: peripheral mobilization during the Arab spring. Am Polit Sci Rev 111(2):379–403

    Article  Google Scholar 

  58. Traag V (2016) Complex contagion of campaign donations. PLoS One 11(4):e0153539

    Article  Google Scholar 

  59. Parigi P, Gong R (2014) From grassroots to digital ties: a case study of a political consumerism movement. J Consum Cult 14(2):236–253

    Article  Google Scholar 

  60. Parkinson S (2013) Organizing rebellion: rethinking high-risk mobilization and social networks in war. Am Polit Sci Rev 107(3):418–432

    Article  MathSciNet  Google Scholar 

  61. Yasseri T, Hale S, Margetts H (2014) Modeling the rise in Internet-based petitions. arXiv. https://arxiv.org/abs/1308.0239

  62. Siegel D (2009) Social networks and collective action. Am J Polit Sci 53(1):122–138

    Article  Google Scholar 

  63. Siegel D (2011) When does repression work? Collective action in social networks. J Politics 73(4):993–1010

    Article  Google Scholar 

  64. DellaPosta D, Nee V, Opper S (2017) Endogenous dynamics of institutional change. Ration Soc 29(1):5–48

    Article  Google Scholar 

  65. Catlaw, T., and Stout, M. (2016). Governing small-town America today: the promise and dilemma of dense networks. The American Association for Public Administration, Washington, 76(2), 225–229

    Google Scholar 

  66. Pan W, Ghoshal G, Krumme C, Cebrian M, Pentland A (2013) Urban characteristics attributable to density-driven tie formation. Nat Commun 4:1961

    Article  ADS  Google Scholar 

  67. Barash V, Cameron C, Macy M (2012) Critical phenomena in complex contagions. Soc Networks 34:451–461

    Article  Google Scholar 

  68. Takaguchi T, Masuda N, Holme P (2013) Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics. PLoS One 8(7):e68629

    Article  ADS  Google Scholar 

  69. Sun E, Rosenn I, Marlow C, Lento T (2009) Gesundheit! modeling contagion through Facebook news feed. In: Third international AAAI conference on weblogs and social media

    Google Scholar 

  70. Gleeson JP, Cahalane DJ (2007) Seed size strongly affects cascades on random networks. Phys Rev E Stat Nonlin Soft Matter Phys 75:056103

    Article  ADS  Google Scholar 

  71. Dodds PS, Payne JL (2009) Analysis of a threshold model of social contagion on degree-correlated networks. Phys Rev E Stat Nonlin Soft Matter Phys 79(6 Pt 2):066115

    Article  Google Scholar 

  72. Gleeson JP (2008) Cascades on correlated and modular random networks. Phys Rev E Stat Nonlin Soft Matter Phys 77(4 Pt 2):046117

    Article  ADS  Google Scholar 

  73. Gai P, Kapadia S (2010) Contagion in financial networks. Proc R Soc A 466:2401–2423

    Article  MathSciNet  MATH  ADS  Google Scholar 

  74. Hurd TR, Gleeson JP (2013) On watts cascade model with random link weights. J Complex Netw 1:25–43

    Article  MATH  Google Scholar 

  75. Galstyan A, Cohen P (2007) Cascading dynamics in modular networks. Phys Rev E Stat Nonlin Soft Matter Phys 75(3 Pt 2):036109

    Article  ADS  Google Scholar 

  76. Hackett A, Melnik S, Gleeson JP (2011) Cascades on a class of clustered random networks. Phys Rev E Stat Nonlin Soft Matter Phys 83(5 Pt 2):056107

    Article  ADS  Google Scholar 

  77. Ikeda Y, Hasegawa T, Nemoto K (2010) Cascade dynamics on clustered network. J Phys 221:012013

    Google Scholar 

  78. Backlund VP, Saramaki J, Pan RK (2014) Effects of temporal correlations on cascades: threshold models on temporal networks. Phys Rev E Stat Nonlin Soft Matter Phys 89(6):062815

    Article  Google Scholar 

  79. Karimi K, Holme P (2013) Threshold model of cascades in empirical temporal networks. Phys A 392:3476–3483

    Article  Google Scholar 

  80. Brummitt CD, Lee KM, Goh KI (2012) Multiplexity-facilitated cascades in networks. Phys Rev E Stat Nonlin Soft Matter Phys 85(4 Pt 2):045102

    Article  ADS  Google Scholar 

  81. Lee KM, Brummitt CD, Goh KI (2014) Threshold cascades with response heterogeneity in multiplex networks. Phys Rev E Stat Nonlin Soft Matter Phys 90(6):062816

    Article  Google Scholar 

  82. Yağan O, Gligor V (2012) Analysis of complex contagions in random multiplex networks. Phys Rev E 86:036103

    Article  ADS  Google Scholar 

  83. Shu P, Gao L, Zhao P, Wang W, Stanley H (2017) Social contagions on interdependent lattice networks. Sci Rep 7:44669

    Article  ADS  Google Scholar 

  84. Bassett D, Alderson D, Carlson J (2012) Collective decision dynamics in the presence of external drivers. arXiv. https://arxiv.org/abs/1206.1120

  85. Zhao JH, Zhou HJ, Liu YY (2013) Inducing effect on the percolation transition in complex networks. Nat Commun 4:2412

    Article  Google Scholar 

  86. O’Sullivan D, Keefe G, Fennell P, Gleeson J (2015) Mathematical modeling of complex contagion on clustered networks. Front Phys 8:71

    Google Scholar 

  87. Pastor-Satorras R, Castellano C, Mieghem PV, Vespignani A (2015) Epidemic processes in complex networks. arXiv. https://arxiv.org/abs/1408.2701

  88. Wang W, Shu P, Zhu YX, Tang M, Zhang YC (2015) Dynamics of social contagions with limited contact capacity. Chaos 25(10):103102

    Article  MathSciNet  MATH  ADS  Google Scholar 

  89. Wang W, Tang M, Zhang HF, Lai YC (2015) Dynamics of social contagions with memory of nonredundant information. Phys Rev E Stat Nonlin Soft Matter Phys 92(1):012820

    Article  ADS  Google Scholar 

  90. Perez-Reche FJ, Ludlam JJ, Taraskin SN, Gilligan CA (2011) Synergy in spreading processes: from exploitative to explorative foraging strategies. Phys Rev Lett 106(21):218701

    Article  ADS  Google Scholar 

  91. McCullen N, Rucklidge A, Bale C, Foxon T, Gale W (2013) Multiparameter models of innovation diffusion on complex networks. J Appl Dyn Syst 12:515–532

    Article  MathSciNet  MATH  Google Scholar 

  92. Dodds PS, Harris KD, Danforth CM (2013) Limited imitation contagion on random networks: chaos, universality, and unpredictability. Phys Rev Lett 110(15):158701

    Article  ADS  Google Scholar 

  93. Melnik S, Ward JA, Gleeson JP, Porter MA (2013) Multi-stage complex contagions. Chaos 23:013124

    Article  MathSciNet  ADS  Google Scholar 

  94. Huang W, Zhang I, Xu X, Fu X (2016) Contagion on complex networks with persuasion. Sci Rep 6:23766. https://doi.org/10.1038/srep23766

    Article  ADS  Google Scholar 

  95. Ruan Z, Iniguez G, Karsai M, Kertesz J (2015) Kinetics of social contagion. Phys Rev Lett 115(21):218702

    Article  ADS  Google Scholar 

  96. Kuhlman CJ, Kumar VSA, Marathe MV et al (2015) Inhibiting diffusion of complex contagions in social networks: theoretical and experimental results. Data Min Knowl Disc 29:423. https://doi.org/10.1007/s10618-014-0351-4

    Article  MathSciNet  Google Scholar 

  97. Centola D (2009) Failure in complex networks. J Math Sociol 33:64–68

    Article  MATH  Google Scholar 

  98. Albert R, Jeong H, Barabási A (2000) Error and attack tolerance of complex networks. Nature 406:378–382

    Article  ADS  Google Scholar 

  99. Blume L, Easley D, Kleinberg J, Kleinberg R, Tardos E (2011) Which networks are least susceptible to cascading failures? In: IEEE 52nd annual symposium on foundations of computer science (FOCS)

    Google Scholar 

  100. Myers S, Leskovec J (2013) Clash of the contagions: cooperation and competition in information diffusion. In: IEEE 12th international conference on data mining (ICDM)

    Google Scholar 

  101. Jie R, Qiaoa J, Xub G, Menga Y (2016) A study on the interaction between two rumors in homogeneous complex networks under symmetric conditions. Phys A 454:129–142

    Article  Google Scholar 

  102. Su Y, Zhang X, Liu L et al (2016) Understanding information interactions in diffusion: an evolutionary game-theoretic perspective. Front Comput Sci 10:518. https://doi.org/10.1007/s11704-015-5008-y

    Article  Google Scholar 

  103. Teng C, Gong L, Eecs A, Brunetti C, Adamic L (2012) Coevolution of network structure and content. In: Proceedings of WebSci ‘12 proceedings of the 4th annual ACM web science conference, pp 288–297

    Google Scholar 

  104. Rosenthal SB, Twomey CR, Hartnett AT, Wu HS, Couzin ID (2015) Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion. PNAS 112(15):4690–4695

    Article  ADS  Google Scholar 

  105. Dimaggio P (1997) Culture and cognition. Annu Rev Sociol 23:263–287

    Article  Google Scholar 

  106. Puglisi A, Baronchelli A, Loreto V (2008) Cultural route to the emergence of linguistic categories. PNAS 105(23):7936–7940

    Article  ADS  Google Scholar 

  107. Coman A, Momennejad I, Drach RD, Geana A (2016) Mnemonic convergence in social networks: the emergent properties of cognition at a collective level. PNAS 113(29):8171–8176

    Article  Google Scholar 

  108. Morris S (2000) Contagion. Rev Econ Stud 67:57–78

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  ADS  Google Scholar 

  110. Alvarez-Galvarez J (2015) Network models of minority opinion spreading: using agent-based Modeling to study possible scenarios of social contagion. Soc Sci Comput Rev 34(5):567–581

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA

    Douglas Guilbeault, Joshua Becker & Damon Centola

Authors
  1. Douglas Guilbeault
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joshua Becker
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Damon Centola
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Damon Centola .

Editor information

Editors and Affiliations

  1. Technical University of Denmark, Lyngby, Denmark

    Sune Lehmann

  2. Indiana University, Bloomington, Indiana, USA

    Yong-Yeol Ahn

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Guilbeault, D., Becker, J., Centola, D. (2018). Complex Contagions: A Decade in Review. 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_1

Download citation

Publish with us

Policies and ethics

Search

Navigation