Coevolutionary networks with homophily and heterophily
Abstract
We have investigated a simple coevolutionary network model incorporating three processes-changes of opinions, homophily, and heterophily. In this model, each node holds one of G opinions and changes its opinion, as in the voter model. Homophily is the tendency for connections to form between individuals of the same opinions and heterophily is the opposite effect. If there is no heterophily, this model corresponds to the Holme and Newman model [Phys. Rev. E 74, 056108 (2006)]. We show that the behavior of this model without heterophily can be understood in terms of a mean field approximation. We also find that this model with heterophily exhibits topologically complicated behaviors such as the small-world property.
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Informational influence theory for group polarization holds that agents with moderate opinions may become extreme while interacting in a group.
“This mechanism builds on the idea of informational influence theory [38] for the phenomenon of group polarization, where agents with moderate opinions may become extreme while interacting in a group [31].”
From Modeling echo chambers and polarization dynamics in social networks (2020) · cites this paper as [31]
Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060 · see citing works
Granovetter, M. S. (1973) · American Journal of Sociology · doi:10.1086/225469 · Cited by 40,491 · see citing works
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135 · see citing works
Statistical mechanics of complex networks
Albert, R., & Barabási, A.-L. (2002) · Reviews of Modern Physics · doi:10.1103/revmodphys.74.47 · Cited by 20,471 · see citing works
The Structure and Function of Complex Networks
Newman, M. E. J. (2003) · SIAM Review · doi:10.1137/s003614450342480 · Cited by 18,719 · see citing works
Complex networks: structure and dynamics
BOCCALETTI, S., LATORA, V, MORENO, Y., CHAVEZ, M., & HWANG, D. (2006) · Physics Reports · doi:10.1016/j.physrep.2005.10.009 · Cited by 11,010 · see citing works
Epidemic Spreading in Scale-Free Networks
Pastor‐Satorras, R., & Vespignani, A. (2001) · Physical Review Letters · doi:10.1103/physrevlett.86.3200 · Cited by 5,773 · see citing works
Dorogovtsev, S. N., & Mendes, J. F. F. (2002) · Advances In Physics · doi:10.1080/00018730110112519 · Cited by 3,231 · see citing works
Classes of small-world networks
Amaral, L. A. N., Scala, A., Barthélémy, M., & Stanley, H. E. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.200327197 · Cited by 3,051 · see citing works
Synchronization in Small-World Systems
Barahona, M., & Pecora, L. M. (2002) · Physical Review Letters · doi:10.1103/physrevlett.89.054101 · Cited by 1,648 · see citing works
Immunization of complex networks
Pastor‐Satorras, R., & Vespignani, A. (2002) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.65.036104 · Cited by 1,296 · see citing works
A Propositional Inventory for New Diffusion Research
Gatignon, H., & Robertson, T. S. (1985) · Journal of Consumer Research · doi:10.1086/209021 · Cited by 1,209 · see citing works
Epidemic Dynamics on an Adaptive Network
Groß, T., D’Lima, C. J. D., & Blasius, B. (2006) · Physical Review Letters · doi:10.1103/physrevlett.96.208701 · Cited by 900 · see citing works
Adaptive coevolutionary networks: a review
Gross, T., & Blasius, B. (2007) · Journal of The Royal Society Interface · doi:10.1098/rsif.2007.1229 · Cited by 862 · see citing works
Scale-Free Networks from Varying Vertex Intrinsic Fitness
Caldarelli, G., Capocci, A., De Los Rios, P., & Muñoz, M. A. (2002) · Physical Review Letters · doi:10.1103/physrevlett.89.258702 · Cited by 794 · see citing works
Homophily-Heterophily: Relational Concepts for Communication Research
Rogers, E. M., & Bhowmik, D. K. (1970) · Public Opinion Quarterly · doi:10.1086/267838 · Cited by 650 · see citing works
Nonequilibrium phase transition in the coevolution of networks and opinions
Holme, P., & Newman, M. E. J. (2006) · Physical Review E · doi:10.1103/physreve.74.056108 · Cited by 621 · see citing works
Voter model on heterogeneous graphs.
Sood, V., & Redner, S. (2004) · Physical Review Letters · doi:10.1103/physrevlett.94.178701 · Cited by 620 · see citing works
Fast Response and Temporal Coherent Oscillations in Small-World Networks
Lago-Fernández, L. F., Huerta, R., Corbacho, F., & Siguenza, J. A. (2000) · Physical Review Letters · doi:10.1103/physrevlett.84.2758 · Cited by 572 · see citing works
Vázquez, A. (2003) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.67.056104 · Cited by 571 · see citing works
Dorogovtsev, S. N., Goltsev, A. V., & Mendes, J. F. F. (2002) · Physical Review E · doi:10.1103/physreve.65.066122 · Cited by 540 · see citing works
Coevolution of dynamical states and interactions in dynamic networks
Zimmermann, M., Eguı́luz, V. M., & Miguel, M. S. (2004) · Physical Review E · doi:10.1103/physreve.69.065102 · Cited by 504 · see citing works
Dynamical Weights and Enhanced Synchronization in Adaptive Complex Networks
Zhou, C., & Kurths, J. (2006) · Physical Review Letters · doi:10.1103/physrevlett.96.164102 · Cited by 398 · see citing works
Critical behavior of propagation on small-world networks
Zanette, D. H. (2001) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.64.050901 · Cited by 381 · see citing works
Growing scale-free networks with small-world behavior
Klemm, K., & Eguı́luz, V. M. (2002) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.65.057102 · Cited by 342 · see citing works
Emergence of a Small World from Local Interactions: Modeling Acquaintance Networks
Davidsen, J., Ebel, H., & Bornholdt, S. (2002) · Physical Review Letters · doi:10.1103/physrevlett.88.128701 · Cited by 308 · see citing works
Self-Sustained Activity in a Small-World Network of Excitable Neurons
Roxin, A., Riecke, H., & Solla, S. A. (2004) · Physical Review Letters · doi:10.1103/physrevlett.92.198101 · Cited by 303 · see citing works
Topological Evolution of Dynamical Networks: Global Criticality from Local Dynamics
Bornholdt, S., & Rohlf, T. (2000) · Physical Review Letters · doi:10.1103/physrevlett.84.6114 · Cited by 277 · see citing works
Correlation models for childhood epidemics
Keeling, M. J., Rand, D. A. J., & Morris, A. (1997) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.1997.0159 · Cited by 216 · see citing works
Ising model in small-world networks
Herrero, C. P. (2002) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.65.066110 · Cited by 167 · see citing works
Liu, W. T., & Duff, R. W. (1972) · Public Opinion Quarterly · doi:10.1086/268018 · Cited by 141 · see citing works
Self-organized critical neural networks
Bornholdt, S., & Röhl, T. (2003) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.67.066118 · Cited by 126 · see citing works
Dynamics of Networking Agents Competing for High Centrality and Low Degree
Holme, P., & Ghoshal, G. (2006) · Physical Review Letters · doi:10.1103/physrevlett.96.098701 · Cited by 83 · see citing works
Connection topology dependence of synchronization of neural assemblies on class 1 and 2 excitability
Lago-Fernández, L. F., Corbacho, F., & Huerta, R. (2001) · Neural Networks · doi:10.1016/s0893-6080(01)00032-6 · Cited by 31 · see citing works
Performance of excitable small-world networks of Bonhoeffer-van der Pol-FitzHugh-Nagumo oscillators
Vragović, I., Louis, E., & Dı́az-Guilera, A. (2006) · Europhysics Letters (EPL) · doi:10.1209/epl/i2006-10351-x · Cited by 9 · see citing works
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Modeling echo chambers and polarization dynamics in social networks
Baumann, F., Lorenz-Spreen, P., Sokolov, I. M., & Starnini, M. (2020) · Physical Review Letters · doi:10.1103/physrevlett.124.048301 · Cited by 427 · see citing works
- Authors
- Kimura, D., & Hayakawa, Y.
- Affiliations
- Tohoku University (JP)
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2008-07-07
- Volume
- 78
- Issue
- 1
- Pages
- 016103-016103
- ISSN
- 1539-3755 (ISSN-L)
- 1550-2376
- OpenAlex
- W2040467035
- Cited by
- 107
- References
- 35
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 9 · 2023: 5 · 2022: 6 · 2021: 9 · 2020: 11 · 2019: 6 · 2018: 6 · 2017: 6 · 2016: 4 · 2015: 5 · 2014: 9 · 2013: 10 · 2012: 6
- FWCI
- 1.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Physical Review E (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
- Keywords
- homophily, heterophily, opinion dynamics, voter model, mean-field approximation, small-world networks, network topology, social networks
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