Skip to main content
SpringerLink
Log in

Synchrony in Social Groups and Its Benefits

  • Chapter
  • First Online:
Handbook of Human Computation

Abstract

In recent years, social synchrony has attracted much attention from different research areas including biology, physics, psychology, and engineering. It is widely believed that synchrony, as an outcome of evolutionary selection, can increase the cohesion of social groups and thus lead them to perform better when dealing with complex tasks. This chapter briefly reviews several quantitative aspects of social synchrony, including how to measure and how to model it, the impact on it of the social network structure underlying the group, and its benefits to cooperation and productivity. We provide a case study of social synchrony among software developers in Apache, a distributed Open Source Software (OSS) project. In it, we illustrate how one could quantitatively study aspects of social synchrony. The results suggest that Apache software developers synchronize their work with each other, and work together in larger groups in relatively short periods. Such working synchrony increases productivity, in terms of the number of lines of code produced, and improves the efficiency of coordination among developers, in terms of communication overhead.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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

References

  • Acebrón JA, Bonilla LL, Vicente CJP, Ritort F, Spigler R (2005) The Kuramoto model: a simple paradigm for synchronization phenomena. Rev Mod Phys 77(1):137–185

    Article  Google Scholar 

  • Aghdam MH, Ghasem-Aghaee N, Basiri ME (2009) Text feature selection using ant colony optimization. Expert Syst Appl 36(3):6843–6853

    Article  Google Scholar 

  • Anthony M, Bartlett PL (2009) Neural network learning: theoretical foundations. Cambridge University Press, Cambridge

    Google Scholar 

  • Arenas A, Díaz-Guilera A, Pérez-Vicente CJ (2006) Synchronization reveals topological scales in complex networks. Phys Rev Lett 96(11):114102

    Article  Google Scholar 

  • Arenas A, Díaz-Guilera A, Kurths J, Moreno Y, Zhou C (2008) Synchronization in complex networks. Phys Rep 469(3):93–153

    Article  MathSciNet  Google Scholar 

  • Barabási A-L, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512

    Article  MathSciNet  Google Scholar 

  • Barahona M, Pecora LM (2002) Synchronization in small-world systems. Phys Rev Lett 89(5):054101

    Article  Google Scholar 

  • Beard RW, Hadaegh FY (2001) A Coordination architecture for spacecraft formation control. IEEE Trans Control Syst Technol 9(6):777–790

    Article  Google Scholar 

  • Blaabjerg F, Teodorescu RE, Liserre M, Timbus AV (2006) Overview of control and grid synchronization for distributed power generation systems. IEEE Trans Ind Electron 53(5):1398–1409

    Article  Google Scholar 

  • Boccaletti S, Ivanchenko M, Latora V, Pluchino A, Rapisarda A (2007) Detecting complex network modularity by dynamical clustering. Phys Rev E 75(4):045102(R)

    Google Scholar 

  • Chatterjee S, Price B (1991) Regression analysis by example. Wiley, New York

    Google Scholar 

  • Chen J, Lu J-A, Zhan C, Chen G (2012) Laplacian spectra and synchronization processes on complex networks. In: Thai MT, Pardalos PM (eds) Handbook of optimization in complex networks: theory and applications. Springer, Heidelberg, pp 81–113

    Chapter  Google Scholar 

  • Chiang TC, Zheng D (2010) An empirical analysis of herd behavior in global stock markets. J Bank Financ 34(8):1911–1921

    Article  Google Scholar 

  • Choudhury MD, Sundaram H, John A, Seligmann DD (2009) Social synchrony predicting mimicry of user actions in online social media. In: The proceedings of the 2009 international conference on computational science and engineering, Vancouver, Canada, pp 151–158

    Google Scholar 

  • Costa LF, Rodrigues FA, Travieso G, Boas PRV (2007) Characterization of complex networks: a survey of measurements. Adv Phys 56(1):167–242

    Article  Google Scholar 

  • Crick C, Munz M, Scassellati B (2006) Synchronization in social tasks: robotic drumming. In: The proceedings of the 15th IEEE international symposium on robot and human interactive communication, Hatfiled, UK, pp 97–102

    Google Scholar 

  • Deneubourg JL, Pasteels JM, Verhaeghe JC (1983) Probabilistic behaviour in ants: a strategy of errors? J Theor Biol 105(2):259–271

    Article  Google Scholar 

  • Donetti L, Hurtado PI, Muñoz MA (2003) Entangled networks, synchronization, and optimal network topology. Phys Rev Lett 95(18):188701

    Article  Google Scholar 

  • Dorigo M, Blum C (2005) Ant colony optimization theory: a survey. Theor Comput Sci 344:243–278

    Article  MathSciNet  MATH  Google Scholar 

  • Dorigo M, Maniezzo V, Colorni A (1996) Ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern Part B: Cybern 26(1):29–41

    Article  Google Scholar 

  • Emlen JJT (1952) Flocking behavior in birds. The Auk 69(2):160–170

    Article  Google Scholar 

  • Fæevik G, Tjentland K, Løvik S, Andersen IL, Bøe KE (2008) Resting pattern and social behaviour of dairy calves housed in pens with different sized lying areas. Appl Anim Behav Sci 114:54–64

    Article  Google Scholar 

  • Fortunato S (2010) Community detection in graphs. Phys Rep 486(3–5):75–174

    Article  MathSciNet  Google Scholar 

  • Freeman W (2000) A neurobiological role of music in social bonding. In: Wallin NL, Merker B, Brown S (eds) The origins of music. MIT, Cambridge, pp 411–424

    Google Scholar 

  • French R, Schermerhorn JR, Rayner C, Rees G, Rumbles S, Hunt JG, Osborn RN (2008) Organizational behaviour. Wiley, New York

    Google Scholar 

  • Fries P (2005) A mechanism for cognitive dynamics: neuronal communication through neuronal coherence. TRENDS Cogn Sci 9(10):474–480

    Article  Google Scholar 

  • Gaing Z-L (2003) Particle swarm optimization to solving the economic dispatch considering the generator constraints. IEEE Trans Power Syst 18(3):1187–1195

    Article  Google Scholar 

  • Girvan M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci USA 99(12):7821–7826

    Article  MathSciNet  MATH  Google Scholar 

  • Gómez-Gardeñes J, Moreno Y, Arenas A (2007) Paths to synchronization on complex networks. Phys Rev Lett 98(3):034101

    Article  Google Scholar 

  • Gonzales AL, Hancock JT, Pennebaker JW (2010) Language style matching as a predictor of social dynamics in small groups. Commun Res 37(1):3–19

    Article  Google Scholar 

  • Haken H (2004) Synergetics: introduction and advanced topics. Springer, Heidelberg

    Book  Google Scholar 

  • Hong H, Kim BJ, Choi MY, Park H (2004) Factors that predict better synchronizability on complex networks. Phys Rev E 69(6):067105

    Article  Google Scholar 

  • Hove MJ, Risen JL (2009) It’s all in the timing: interpersonal synchrony increases affiliation. Soc Cogn 27:949–960

    Article  Google Scholar 

  • http://mathworld.wolfram.com/CageGraph.html

  • Hummel D (1983) Aerodynamic aspects of formation flight in birds. J Theor Biol 104(3):321–347

    Article  Google Scholar 

  • Kuramoto T, Yamagishi H (1990) Physiological anatomy, burst formation, and burst frequency of the cardiac ganglion of crustaceans. Physiol Zool 63(1):102–116

    Google Scholar 

  • Lakin JL, Jefferis VE, Cheng CM, Chartrand TL (2003) The chameleon effect as social glue: evidence for the evolutionary significance of nonconscious mimicry. J Nonverbal Behav 27:145–162

    Article  Google Scholar 

  • Lehmann J, Gonçalves B, Ramasco JJ, Cattuto C (2012) Dynamical classes of collective attention in Twitter. In: The proceedings of the 2012 international world wide web conference committee, Lyon, pp 251–260

    Google Scholar 

  • Lerman K, Ghosh R (2012) Network structure, topology, and dynamics in generalized models of synchronization. Phys Rev E 86(2):026108

    Article  Google Scholar 

  • Lewis SM, Cratsley CK (2008) Flash signal evolution, mate choice, and predation in fireflies. Annu Rev Entomol 53:293–321

    Article  Google Scholar 

  • Li C, Sun W, Kurths J (2007) Synchronization between two coupled complex networks. Phys Rev E 76(4):046204

    Article  Google Scholar 

  • Li D, Leyva I, Almendral JA, Sendiña-Nadal I, Buldú JM, Havlin S, Boccaletti S (2008) Synchronization interfaces and overlapping communities in complex networks. Phys Rev Lett 101(16):168701

    Article  Google Scholar 

  • Lü J, Chen G (2005) A time-varying complex dynamical network model and its controlled synchronization criteria. IEEE Trans Autom Control 50(6):841–846

    Article  Google Scholar 

  • Macrae CN, Duffy OK, Miles LK, Lawrence J (2008) A case of hand waving: action synchrony and person perception. Cognition 109:152–156

    Article  Google Scholar 

  • Merkle D, Middendorf M, Schmeck H (2002) Ant colony optimization for resource-constrained project scheduling. IEEE Trans Evol Comput 6(4):333–346

    Article  Google Scholar 

  • Mirollo RE, Strogatz SH (1990) Synchronization of pulse-coupled biological oscillators. SIAM J Appl Math 50(6):1645–1662

    Article  MathSciNet  MATH  Google Scholar 

  • Moon BS (2001) A gaussian smoothing algorithm to generate trend curves. Korean J Comput Appl Math 8(3):507–518

    MathSciNet  MATH  Google Scholar 

  • Motter AE, Zhou C, Kurths J (2005) Network synchronization, diffusion, and the paradox of heterogeneity. Phys Rev E 71(1):016116

    Article  Google Scholar 

  • Müller V, Lindenberger U (2011) Cardiac and respiratory patterns synchronize between persons during choir singing. PLoS One 6(9):e24893

    Article  Google Scholar 

  • Navlakha S, Bar-Joseph Z (2011) Algorithms in nature: the convergence of systems biology and computational thinking. Mol Syst Biol. doi:10.1038/msb.2011.78

    Google Scholar 

  • Neda Z et al (2000) Self-organizing processes: the sound of many hands clapping. Nature 403:849–850

    Article  Google Scholar 

  • Nishikawa T, Motter AE, Lai Y-C, Hoppensteadt FC (2003) Heterogeneity in oscillator networks: are smaller worlds easier to synchronize? Phys Rev Lett 91(1):014101

    Article  Google Scholar 

  • Otte D (1980) On theories of flash synchronization in fireflies. Am Nat 116(4):587–590

    Article  Google Scholar 

  • Oh E, Rho K, Hong H, Kahng B (2005) Modular synchronization in complex networks. Phys Rev E 72(4):047101

    Article  Google Scholar 

  • Paladino MP, Mazzurega M, Pavani F, Schubert TW (2010) Synchronous multisensory stimulation blurs self-other boundaries. Psychol Sci 21:1202–1207

    Article  Google Scholar 

  • Park K, Lai Y-C, Gupte S (2006) Synchronization in complex networks with a modular structure. Chaos 16(1):015105

    Article  MathSciNet  Google Scholar 

  • Pinzger M, Gall HC (2010) Dynamic analysis of communication and collaboration in OSS projects. In: Collaborative software engineering. Springer, Heidelberg, pp 265–284

    Google Scholar 

  • Poli R, Kennedy J, Blackwell T (2007) Particle swarm optimization. Swarm Intell 1(1):33–57

    Article  MATH  Google Scholar 

  • Posnett D, D’Souza R, Devanbu P, Filkov V (2013) Dual ecological measures of focus for software development. In: The proceedings of the 2013 international conference of software engineering, San Francisco

    Google Scholar 

  • Ravasz E, Somera AL, Mongru DA, Oltvai ZN, Barabási A-L (2002) Hierarchical organization of modularity in metabolic networks. Science 297(5586):1551–1555

    Article  Google Scholar 

  • Scharfstein DS, Stein JC (1990) Herd behavior and investment. Am Econ Rev 80(3):465–479

    Google Scholar 

  • Schweitzer F, Garcia D (2010) An agent-based model of collective emotions in online communities. Eur Phys J B 77(4):533–545

    Article  Google Scholar 

  • Shaw E (1978) Schooling fishes: the school, a truly egalitarian form of organization in which all members of the group are alike in influence, offers substantial benefits to its participants. Am Sci 66(2):166–175

    Google Scholar 

  • Siegfried WR, Underhill LG (1975) Flocking as an anti-predator strategy in doves. Anim Behav 23:504–508

    Article  Google Scholar 

  • Singh KP, Basant A, Malik A, Jain G (2009) Artificial neural network modeling of the river water quality-a case study. Ecol Model 220(6):888–895

    Article  Google Scholar 

  • Sullivan RT (1981) Insect swarming and mating. Fla Entomol 64(1):44–65

    Article  Google Scholar 

  • Sun J, Bollt EM, Porter MA, Dawkins MS (2011) A mathematical model for the dynamics and synchronization of cows. Phys D: Nonlinear Phenom 240(19):1497–1509

    Article  MathSciNet  MATH  Google Scholar 

  • Valdesolo P, Ouyang J, DeSteno D (2010) The rhythm of joint action: synchrony promotes cooperative ability. J Exp Soc Psychol 46(4):693–695

    Article  Google Scholar 

  • Vellido A, Lisboa PJG, Vaughan J (1999) Neural networks in business: a survey of applications. Expert Syst Appl 17:51–70

    Article  Google Scholar 

  • Wang XF, Chen G (2002) Pinning control of scale-free dynamical networks. Phys A: Stat Mech Appl 310(3–4):521–531

    Article  Google Scholar 

  • Wiltermuth SS, Heath C (2009) Synchrony and cooperation. Psychol Sci 20:1–5

    Google Scholar 

  • Woolley AW, Chabris CF, Pentland A, Hashmi N, Malone TW (2010) Evidence for a collective intelligence factor in the performance of human groups. Science 330(6004):686–688

    Article  Google Scholar 

  • Xuan Q, Li Y, Wu T-J (2006) Growth model for complex networks with hierarchical and modular structures. Phys Rev E 73(3):036105

    Article  MATH  Google Scholar 

  • Xuan Q, Li Y, Wu T-J (2009) Optimal symmetric networks in terms of minimizing average shortest path length and their sub-optimal growth model. Phys A: Stat Mech Appl 388(7):1257–1267

    Article  Google Scholar 

  • Xuan Q, Gharehyazie M, Devanbu P, Filkov V (2012) Measuring the effect of social communications on individual working rhythms: a case study of open source software. In: The proceedings of 2012 ASE/IEEE international conference on social informatics, Washington, DC

    Google Scholar 

  • Yan F, Chen G (2013) Distributed consensus and coordination control of networked multi-agent systems. In: Kocarev L (ed) Consensus and synchronization in complex networks. Springer, Heidelberg, pp 51–68

    Chapter  Google Scholar 

  • Yu W, DeLellis P, Chen G, Bernardo MD, Kurths J (2012) Distributed adaptive control of synchronization in complex networks. IEEE Trans Autom Control 57(8):2153–2158

    Article  Google Scholar 

  • Zhou T, Zhao M, Chen G, Yan G, Wang B-H (2007) Phase synchronization on scale-free networks with community structure. Phys Lett A 368(6):431–434

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge support from the Air Force Office of Scientific Research, award FA955-11-1-0246. QX acknowledges support from the National Natural Science Foundation of China (Grants No. 61004097 and No. 612732122).

Author information

Authors and Affiliations

  1. University of California, Davis, CA, 95616-8562, USA

    Qi Xuan & Vladimir Filkov

  2. Zhejiang University of Technology, Hangzhou, 310023, China

    Qi Xuan

Authors
  1. Qi Xuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vladimir Filkov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qi Xuan .

Editor information

Editors and Affiliations

  1. ThinkSplash, LLC, Fairfax, Virginia, USA

    Pietro Michelucci

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this chapter

Cite this chapter

Xuan, Q., Filkov, V. (2013). Synchrony in Social Groups and Its Benefits. In: Michelucci, P. (eds) Handbook of Human Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8806-4_64

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-8806-4_64

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-8805-7

  • Online ISBN: 978-1-4614-8806-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation