The DOI matches its Crossref record; 39 of the 40 references it cites were found in a registry or an index.
Small Worlds and Cultural Polarization
Open accessAbstract
Building on Granovetter's theory of the “strength of weak ties,” research on “small-world” networks suggests that bridges between clusters in a social network (long-range ties) promote cultural diffusion, homogeneity, and integration. We show that this macro-level implication of network structure depends on hidden micro-level assumptions. Using a computational model similar to earlier studies, we find that ties between clusters facilitate cultural convergence under the micro-level assumptions of assimilation and attraction to similar others. However, these assumptions also have negative counterparts—differentiation and xenophobia. We found that when these negative possibilities are no longer assumed away, the effect of long-range ties reverses: Even very small amounts of contact between highly clustered communities sharply increased polarization at the population level. [An appendix to this article is featured as an online supplement at the publisher's website.]
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Another class of models describe polarization by introducing repulsive interactions, in which users reject opinions that differ from their own [24-26], but this mechanism combined with homophily leads to a decrease of polarization [27, 28].”
From Modeling echo chambers and polarization dynamics in social networks (2020) · cites this paper as [25]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
Granovetter, M. S. (1973) · American Journal of Sociology · doi:10.1086/225469 · Cited by 40,491
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
Birds of a Feather: Homophily in Social Networks
McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001) · Annual Review of Sociology · doi:10.1146/annurev.soc.27.1.415 · Cited by 18,567
The World Is Flat: A Brief History of the Twenty-First Century
Ikenberry, G. J., & Friedman, T. L. (2005) · Foreign Affairs · doi:10.2307/20031715 · Cited by 4,210
Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation
Hegselmann, R., & Krause, U. (2002) · RePEc: Research Papers in Economics · Cited by 2,366
The Dissemination of Culture: A Model with Local Convergence and Global Polarization
Axelrod, R. (1997) · Journal of Conflict Resolution · doi:10.1177/0022002797041002001 · Cited by 1,918
Complex Contagions and the Weakness of Long Ties
Centola, D., & Macy, M. (2007) · American Journal of Sociology · doi:10.1086/521848 · Cited by 1,878
Self-citationSocial Pressures in Informal Groups
Festinger, L., Schachter, S., & Back, K. (1950) · The American Catholic Sociological Review · doi:10.2307/3707362 · Cited by 1,831
Networks, Dynamics, and the Small‐World Phenomenon
Watts, D. J. (1999) · American Journal of Sociology · doi:10.1086/210318 · Cited by 1,510
Research works printed but not linked: 5
- Harary F., 1959, Studies in Social Power, 168
- Hegselmann R., 2002, Journal of Artificial Societies and Social Simulation, 5
- Klemm K., 2003, Physical Review E, 67
- Klemm K., 2003, Physical Review E, 67
- Latané B., 1997, Progress in Communication Science: Persuasion, 43
Cited by
Sorted by citations
Models of Social Influence: Towards the Next Frontiers
Flache, A., Mäs, M., Feliciani, T., Chattoe-Brown, E., Deffuant, G., Huet, S., & Lorenz, J. (2017) · Journal of Artificial Societies and Social Simulation · doi:10.18564/jasss.3521 · Cited by 601
Self-citationA tutorial on modeling and analysis of dynamic social networks. Part I
Proskurnikov, A. V., & Tempo, R. (2017) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2017.03.002 · Cited by 577
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
Novel Multidimensional Models of Opinion Dynamics in Social Networks
Parsegov, S. E., Proskurnikov, A. V., Tempo, R., & Friedkin, N. E. (2016) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2016.2613905 · Cited by 402
Opinion Dynamics in Social Networks With Hostile Camps: Consensus vs. Polarization
Proskurnikov, A. V., Matveev, A. S., & Cao, M. (2015) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2015.2471655 · Cited by 387
Network science on belief system dynamics under logic constraints
Friedkin, N. E., Proskurnikov, A. V., Tempo, R., & Parsegov, S. E. (2016) · Science · doi:10.1126/science.aag2624 · Cited by 374
DellaPosta, D., Shi, Y., & Macy, M. (2015) · American Journal of Sociology · doi:10.1086/681254 · Cited by 440
Self-citationA tutorial on modeling and analysis of dynamic social networks. Part II
Proskurnikov, A. V., & Tempo, R. (2018) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2018.03.005 · Cited by 303
How digital media drive affective polarization through partisan sorting
Törnberg, P. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2207159119 · Cited by 288
“Focusing on polarization as the divergence over single attributes, models found that negative influence can lead to bipolarization—that is, division into two divergent groups—even when there are initially no agents with extreme opinions (86, 108, 109).”
BackgroundGimpel, J. G., & Hui, I. S. (2015) · Political Geography · doi:10.1016/j.polgeo.2014.11.003 · Cited by 228
Mäs, M., & Flache, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074516 · Cited by 226
Self-citationPluralistic Collapse: The “Oil Spill” Model of Mass Opinion Polarization
DellaPosta, D. (2020) · American Sociological Review · doi:10.1177/0003122420922989 · Cited by 219
How Empathic Concern Fuels Political Polarization
Simas, E. N., Clifford, S., & Kirkland, J. H. (2019) · American Political Science Review · doi:10.1017/s0003055419000534 · Cited by 219
Agent‐based models in sociology
Bianchi, F., & Squazzoni, F. (2015) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.1356 · Cited by 160
Anticonformity or Independence?—Insights from Statistical Physics
Nyczka, P., & Sznajd-Weron, K. (2013) · Journal of Statistical Physics · doi:10.1007/s10955-013-0701-4 · Cited by 139
Preventing extreme polarization of political attitudes
Axelrod, R., Daymude, J. J., & Forrest, S. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2102139118 · Cited by 154
A Broken Public? Americans’ Responses to the Great Recession
Brooks, C., & Manza, J. (2013) · American Sociological Review · doi:10.1177/0003122413498255 · Cited by 152
Opinion polarization by learning from social feedback
Banisch, S., & Olbrich, E. (2018) · Journal of Mathematical Sociology · doi:10.1080/0022250x.2018.1517761 · Cited by 132
Niche diversity can explain cross-cultural differences in personality structure
Smaldino, P. E., Lukaszewski, A. W., Rueden, C. R. V., & Gurven, M. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0730-3 · Cited by 117
Opinion polarization by learning from social feedback
Banisch, S., & Olbrich, E. (2019) · MPG.PuRe (Max Planck Society) · Cited by 107
Rawlings, C. M., & Childress, C. (2019) · American Journal of Sociology · doi:10.1086/703203 · Cited by 104
Discrepancy and Disliking Do Not Induce Negative Opinion Shifts
Takács, K., Flache, A., & Mäs, M. (2016) · PLOS ONE · doi:10.1371/journal.pone.0157948 · Cited by 97
Self-citationDisambiguation of social polarization concepts and measures
Bramson, A., Grim, P., Singer, D. J., Fisher, S., Berger, W., Sack, G., & Flocken, C. (2016) · The Journal of Mathematical Sociology · doi:10.1080/0022250x.2016.1147443 · Cited by 96
Ideological and Temporal Components of Network Polarization in Online Political Participatory Media
García, D., Abisheva, A., Schweighofer, S., Serdült, U., & Schweitzer, F. (2015) · Policy & Internet · doi:10.1002/poi3.82 · Cited by 91
Diversity and trust: The role of shared values
Beugelsdijk, S., & Klasing, M. J. (2015) · Journal of Comparative Economics · doi:10.1016/j.jce.2015.10.014 · Cited by 90
Local Convergence and Global Diversity
Flache, A., & Macy, M. W. (2011) · Journal of Conflict Resolution · doi:10.1177/0022002711414371 · Cited by 87
Self-citationLocal Convergence and Global Diversity: From Interpersonal to Social InfluencePreprint
Flache, A., & Macy, M. W. (2008) · arXiv (Cornell University) · doi:10.48550/arxiv.0808.2710 · Cited by 78
Self-citationHow can you capture cultural dynamics?
Kashima, Y. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00995 · Cited by 84
Persisting technological boundaries: Social interactions, cognitive correlations and polarization
Roux, V., Bril, B., Cauliez, J., Goujon, A.-L., Lara, C., Manen, C., de Saulieu, G., & Zangato, É. (2017) · Journal of Anthropological Archaeology · doi:10.1016/j.jaa.2017.09.004 · Cited by 77
Will, M., Groeneveld, J., Frank, K., & Müller, B. H. (2020) · Socio-Environmental Systems Modeling · doi:10.18174/sesmo.2020a16325 · Cited by 74
Agent-Based Models for Opinion Formation: A Bibliographic Survey
Mastroeni, L., Vellucci, P., & Naldi, M. (2019) · IEEE Access · doi:10.1109/access.2019.2913787 · Cited by 64
Alizadeh, M., Weber, I. G., Cioffi‐Revilla, C. A., Fortunato, S., & Macy, M. W. (2019) · EPJ Data Science · doi:10.1140/epjds/s13688-019-0193-9 · Cited by 72
Self-citationA model of social influence on body mass index
Hammond, R. A., & Ornstein, J. T. (2014) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.12344 · Cited by 67
A model of opinion and propagation structure polarization in social media
Prasetya, H. A., & Murata, T. (2020) · Computational Social Networks · doi:10.1186/s40649-019-0076-z · Cited by 62
Layered social influence promotes multiculturality in the Axelrod model
Battiston, F., Nicosia, V., Latora, V., & Miguel, M. S. (2017) · Scientific Reports · doi:10.1038/s41598-017-02040-4 · Cited by 54
A general framework to link theory and empirics in opinion formation models
Kozitsin, I. (2022) · Scientific Reports · doi:10.1038/s41598-022-09468-3 · Cited by 56
Glamorizing rampage online: School shooting fan communities on YouTube
Oksanen, A., E.Hawdon, J., & Räsänen, P. (2014) · Technology in Society · doi:10.1016/j.techsoc.2014.08.001 · Cited by 51
A Weighted Balance Model of Opinion Hyperpolarization
Schweighofer, S., Schweitzer, F., & García, D. (2020) · Journal of Artificial Societies and Social Simulation · doi:10.18564/jasss.4306 · Cited by 55
Opinion evolution in time-varying social influence networks with prejudiced agents
Proskurnikov, A. V., Tempo, R., Cao, M., & Friedkin, N. E. (2017) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2017.08.1424 · Cited by 50
Emergence of Polarization in Coevolving Networks
Liu, J., Huang, S., Aden, N. M., Johnson, N. F., & Song, C. (2023) · Physical Review Letters · doi:10.1103/physrevlett.130.037401 · Cited by 46
Ravazzi, C., Dabbene, F., Lagoa, C. M., & Proskurnikov, A. V. (2021) · IEEE Control Systems · doi:10.1109/mcs.2021.3092810 · Cited by 45
Adoption as a social marker: Innovation diffusion with outgroup aversion
Smaldino, P. E., Janssen, M. A., Hillis, V., & Bednar, J. (2016) · Journal of Mathematical Sociology · doi:10.1080/0022250x.2016.1250083 · Cited by 44
Brown, G. D. A., Lewandowsky, S., & Huang, Z. (2022) · Psychological Review · doi:10.1037/rev0000342 · Cited by 44
Consensus, Polarization, and Alignment in the Economics Profession
Gunten, T. S. V., Martin, J. L., & Teplitskiy, M. (2016) · Sociological Science · doi:10.15195/v3.a45 · Cited by 38
Zhang, Y., & Liu, Y. (2019) · Applied Mathematics and Computation · doi:10.1016/j.amc.2019.124667 · Cited by 36
Empirical social triad statistics can be explained with dyadic homophylic interactions
Pham, T. M., Korbel, J., Hanel, R., & Stefan Thurner, A. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2121103119 · Cited by 42
Agent-based computational modelling of social risk responses
Busby, J. S., Onggo, B. S., & Liu, Y. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.12.034 · Cited by 42
Will the Personalization of Online Social Networks Foster Opinion Polarization?Preprint
Mäs, M., & Bischofberger, L. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2553436 · Cited by 39
Consensus and polarization in Altafini's model with bidirectional time-varying network topologies
Proskurnikov, A. V., Matveev, A. S., & Cao, M. (2014) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2014.7039710 · Cited by 35
How, when and where can Spatial Segregation Induce Opinion Polarization? Two Competing Models
Feliciani, T., Flache, A., & Tolsma, J. (2017) · Journal of Artificial Societies and Social Simulation · doi:10.18564/jasss.3419 · Cited by 33
Self-citationGenerative Explanation and Individualism in Agent-Based Simulation
Marchionni, C., & Ylikoski, P. (2013) · Philosophy of the Social Sciences · doi:10.1177/0048393113488873 · Cited by 33
Parsegov, S. E., Proskurnikov, A. V., Tempo, R., & Friedkin, N. E. (2015) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2015.7402757 · Cited by 31
Flache, A. (2018) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-018-9391-1 · Cited by 35
Self-citationRole of voting intention in public opinion polarization
Vázquez, F., Saintier, N., & Pinasco, J. P. (2020) · Physical review. E · doi:10.1103/physreve.101.012101 · Cited by 28
An Argument Communication Model of Polarization and Ideological Alignment
Banisch, S., & Olbrich, E. (2021) · Journal of Artificial Societies and Social Simulation · doi:10.18564/jasss.4434 · Cited by 35
Modeling Information Cocoons in Networked Populations: Insights From Backgrounds and Preferences
Gu, M., Zhao, T.-F., Yang, L., Wu, X.-K., & Chen, W. (2024) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2024.3354508 · Cited by 31
Opinion strength influences the spatial dynamics of opinion formation
Baumgaertner, B. O., Tyson, R. C., & Krone, S. M. (2016) · Journal of Mathematical Sociology · doi:10.1080/0022250x.2016.1205049 · Cited by 27
Integrating Diversity into Distance Research for Added Rigor, Parsimony, and Relevance
Kostova, T., & Beugelsdijk, S. (2021) · Journal of Management Studies · doi:10.1111/joms.12687 · Cited by 25
The roots of polarization in the individual reward system
Lefebvre, G., Deroy, O. D., & Bahrami, B. (2024) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2023.2011 · Cited by 26
The great divide: drivers of polarization in the US public
Böttcher, L., & Gersbach, H. (2020) · EPJ Data Science · doi:10.1140/epjds/s13688-020-00249-4 · Cited by 28
Gunten, T. S. V. (2015) · Theory and Society · doi:10.1007/s11186-015-9253-8 · Cited by 25
MEASURING CULTURAL DYNAMICS THROUGH THE EUROVISION SONG CONTEST
García, D., & Tanase, D. (2013) · Advances in Complex Systems · doi:10.1142/s0219525913500379 · Cited by 28
Multipolar social systems: Measuring polarization beyond dichotomous contexts
Martín-Gutíerrez, S., Losada, J. C., & Benito, R. M. (2023) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2023.113244 · Cited by 29
Opinion Dynamics With Heterogeneous Multiple Interdependent Topics on the Signed Social Networks
He, G. L., Shen, Z., Huang, T., Zhang, W., & Wu, X. (2023) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2023.3281373 · Cited by 23
A New Framework for ABMs Based on Argumentative Reasoning
Gabbriellini, S., & Torroni, P. (2013) · Advances in intelligent systems and computing · doi:10.1007/978-3-642-39829-2_3 · Cited by 25
The great refusal: The west, the rest, and the new regulations on homosexuality, 1970–2015
Ferguson, J. L. (2022) · American Journal of Sociology · doi:10.1086/723107 · Cited by 23
Modeling Confirmation Bias and Peer Pressure in Opinion Dynamics
Liu, L., Wang, X., Chen, X., Tang, S., & Zheng, Z. (2021) · Frontiers in Physics · doi:10.3389/fphy.2021.649852 · Cited by 23
How behaviors spread in dynamic social networks
Zhang, Y., & Wu, Y. (2011) · Computational and Mathematical Organization Theory · doi:10.1007/s10588-011-9105-7 · Cited by 22
On the Coevolution of Stereotype, Culture, and Social Relationships
Joseph, K., Morgan, G. P., Martin, M. K., & Carley, K. M. (2013) · Social Science Computer Review · doi:10.1177/0894439313511388 · Cited by 22
Bounded Confidence under Preferential Flip: A Coupled Dynamics of Structural Balance and Opinions
Parravano, A., Andina‐Díaz, A., & Meléndez-Jímenez, M. A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0164323 · Cited by 21
In the Organization’s Shadow: How Individual Behavior Is Shaped by Organizational Leakage
Brashears, M. E., Genkin, M., & Suh, C. S. (2017) · American Journal of Sociology · doi:10.1086/693703 · Cited by 24
Psychological and Personality Profiles of Political ExtremistsPreprint
Alizadeh, M., Weber, I. G., Cioffi‐Revilla, C. A., Fortunato, S., & Macy, M. W. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1704.00119 · Cited by 31
Self-citationA theoretical framework for polarization as the gradual fragmentation of a divided society
Bliuc, A., Betts, J. M., Vergani, M., Bouguettaya, A., & Cristea, M. (2024) · Communications Psychology · doi:10.1038/s44271-024-00125-1 · Cited by 38
Cerro, C. C. D. (2024) · Applied Network Science · doi:10.1007/s41109-024-00679-3 · Cited by 43
Kang, J., Ha, S., Kang, K., & JEONG, E. (2013) · Journal of Mathematical Sociology · doi:10.1080/0022250x.2011.629063 · Cited by 21
Paths to Polarization: How Extreme Views, Miscommunication, and Random Chance Drive Opinion Dynamics
Turner, M. A., & Smaldino, P. E. (2018) · Complexity · doi:10.1155/2018/2740959 · Cited by 22
Cognitive Authority and the Constraint of Attitude Change in Groups
Rawlings, C. M. (2020) · American Sociological Review · doi:10.1177/0003122420967305 · Cited by 25
Nelson, M., Hess, J. M., Isakson, B. L., & Goodkind, J. R. (2015) · Journal of International Migration and Integration / Revue de l integration et de la migration internationale · doi:10.1007/s12134-015-0441-1 · Cited by 21
FLACHE, A. (2018) · Advances in Complex Systems · doi:10.1142/s0219525918500170 · Cited by 19
Self-citationAgent-based computational models
Flache, A., & Fernandes, C. A. D. M. (2021) · Edward Elgar Publishing eBooks · doi:10.4337/9781789906851.00033 · Cited by 20
Self-citationOpinion dynamics using Altafini's model with a time-varying directed graph
Proskurnikov, A. V., & Cao, M. (2014) · The proceedings of the IEEE Conference on Control Applications/The proceedings of the ... IEEE Conference on Control Applications · doi:10.1109/isic.2014.6967611 · Cited by 20
When is ignorance bliss? Disclosing true information and cascades of norm violation in networks
Mäs, M., & Opp, K. (2016) · Social Networks · doi:10.1016/j.socnet.2016.05.004 · Cited by 19
Differential inequalities in multi-agent coordination and opinion dynamics modeling
Proskurnikov, A. V., & Cao, M. (2017) · Automatica · doi:10.1016/j.automatica.2017.07.065 · Cited by 19
Exploring How Homophily and Accessibility Can Facilitate Polarization in Social Networks
Taylor, C. E., Mantzaris, A. V., & Garibay, I. I. (2018) · Information · doi:10.3390/info9120325 · Cited by 19
Worlds of Agents: Prospects of Agent-Based Modeling for Communication Research
Waldherr, A., Hilbert, M., & González‐Bailón, S. (2021) · Communication Methods and Measures · doi:10.1080/19312458.2021.1986478 · Cited by 20
Using Ego Network Data to Inform Agent-based Models of Diffusion
Smith, J. A., & Burow, J. (2018) · Sociological Methods & Research · doi:10.1177/0049124118769100 · Cited by 18
Opinion dynamics with the increasing peer pressure and prejudice on the signed graph
He, G. L., Zhang, W., Liu, J., & Ruan, H. (2020) · Nonlinear Dynamics · doi:10.1007/s11071-020-05473-1 · Cited by 18
Evolution of clusters in large-scale dynamical networks
Proskurnikov, A. V., & Granichin, O. N. (2018) · Cybernetics and Physics · doi:10.35470/2226-4116-2018-7-3-102-129 · Cited by 18
Diversity and Complementarity of Agent-Based Models in the Social Sciences
Livet, P., Phan∥, D., Sanders, L., & Hamilton, P. (2014) · Revue Française de Sociologie · doi:10.3917/rfs.554.0689 · Cited by 28
Velásquez-Rojas, F., & Vázquez, F. (2018) · Journal of Statistical Mechanics Theory and Experiment · doi:10.1088/1742-5468/aab1b4 · Cited by 17
Banisch, S., & Shamon, H. (2023) · Sociological Methods & Research · doi:10.1177/00491241231186658 · Cited by 15
Opinion Dynamics With Competitive Relationship and Switching Topologies
He, G. L., Ruan, H., Wu, Y., & Liu, J. (2020) · IEEE Access · doi:10.1109/access.2020.3047893 · Cited by 16
Consensus in Multi‐Agent Systems
Proskurnikov, A. V., & Cao, M. (2016) · Wiley eBooks · doi:10.1002/047134608x.w8332 · Cited by 18
Opinion dynamics with emergent collective memory: A society shaped by its own past
Boschi, G., Cammarota, C., & Kühn, R. (2020) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2020.124909 · Cited by 14
Opinion formation and bi-polarization with biased assimilation and homophily
Fu, G., & Zhang, W. (2015) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2015.10.006 · Cited by 15
A Weighted Balance Model of Opinion HyperpolarizationPreprint
Schweighofer, S., Schweitzer, F., & García, D. (2019) · doi:10.31235/osf.io/weg67 · Cited by 15
AN ENERGY-BASED INTERACTION MODEL FOR POPULATION OPINION DYNAMICS WITH TOPIC COUPLING
Noorazar, H. (2017) · Research Exchange (Washington State University) · Cited by 15
Social Boundaries and Networks in the Diffusion of Innovations: a Short Introduction
Roux, V., & Manzo, G. (2018) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-018-9395-x · Cited by 14
Sirrianni, J., Liu, X., & Adams, D. (2018) · IEEE International Conference on Cognitive Computing (ICCC) · doi:10.1109/iccc.2018.00015 · Cited by 14
Spatial opinion dynamics and the effects of two types of mixing
Baumgaertner, B. O., Fetros, P. A., Krone, S. M., & Tyson, R. C. (2018) · Physical review. E · doi:10.1103/physreve.98.022310 · Cited by 14
Metadata
- Authors
- FLACHE, A., & MACY, M. W.
- Affiliations
- University of Groningen (NL)
- Cornell University (US)
- Corresponding author
- FLACHE, ANDREAS
- Venue
- The Journal of Mathematical Sociology
- Publisher
- Informa UK Limited
- Published
- 2011-01-25
- Volume
- 35
- Issue
- 1-3
- Pages
- 146-176
- ISSN
- 0022-250X (ISSN-L)
- 1545-5874
- OpenAlex
- W2005766286
- Cited by
- 237
- References
- 40
- Citations by year
- 2026: 19 · 2025: 16 · 2024: 24 · 2023: 23 · 2022: 15 · 2021: 15 · 2020: 20 · 2019: 17 · 2018: 18 · 2017: 14 · 2016: 12 · 2015: 15 · 2014: 12 · 2013: 13 · 2012: 1
- FWCI
- 7.10
- Type
- journal article
- Language
- en
- Update notices
- correction (2017-05-31)
- Open access
- bronze
- doi.org
- Locations
- Journal of Mathematical Sociology (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (452-04-351)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Sociology and Political Science › Social Capital and Networks
- Keywords
- small-world networks, cultural polarization, cultural diffusion, social network structure, assimilation, xenophobia, differentiation, cultural convergence, Granovetter, computational model
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review