Group interactions modulate critical mass dynamics in social convention
Open accessAbstract
How can minorities of individuals overturn social conventions? The theory of critical mass states that when a committed minority reaches a critical size, a cascade of behavioural changes can occur, overturning apparently stable social norms. Evidence comes from theoretical and empirical studies in which minorities of very different sizes, including extremely small ones, manage to bring a system to its tipping point. Here, we explore this diversity of scenarios by introducing group interactions as a crucial element of realism into a model for social convention. We find that the critical mass necessary to trigger behaviour change can be very small if individuals have a limited propensity to change their views. Moreover, the ability of the committed minority to overturn existing norms depends in a complex way on the group size. Our findings reconcile the different sizes of critical mass found in previous investigations and unveil the critical role of groups in such processes. This further highlights the importance of the emerging field of higher-order networks, beyond pairwise interactions.
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
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?
Social norms can be changed by a few deviants or cultural leaders.
“More specifically, it has been shown that a population’s opinion can be influenced by a few “stubborn individuals”77, and social norms can be changed by a few deviants or cultural leaders78–80.”
From Cooperation without punishment (2023) · cites this paper as [80]
The Abstract and Discussion say that very small committed minorities can overturn social norms; the Discussion gives an example involving a single individual. The paper does not identify these individuals as cultural leaders, and says the individual in its example has no special power or wealth. The claim is supported as to a few people changing norms, but not as to their being cultural leaders. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness
Nishita, M., Park, S.-Y., Nishio, T., Kamizaki, K., Wang, Z., Tamada, K., Takumi, T., Hashimoto, R., Otani, H., Pazour, G. J., et al. (2017) · Scientific Reports · doi:10.1038/s41598-016-0028-x · Cited by 15,947 · see citing works
Fortunato, S. (2010) · Physics Reports · doi:10.1016/j.physrep.2009.11.002 · Cited by 11,293 · see citing works
Maximizing the spread of influence through a social network
Kempe, D., Kleinberg, J. M., & Eva Tardos, D. (2003) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/956750.956769 · Cited by 7,541 · see citing works
Threshold models of collective behavior
Granovetter, M. (1978) · American Journal of Sociology · doi:10.1086/226707 · Cited by 6,072 · see citing works
Statistical physics of social dynamics
Castellano, C., Fortunato, S., & Loreto, V. (2009) · Reviews of Modern Physics · doi:10.1103/revmodphys.81.591 · Cited by 4,119 · see citing works
Micromotives and Macrobehavior
Eaton, B. C., & Schelling, T. C. (1981) · Canadian Journal of Economics/Revue canadienne d économique · doi:10.2307/134812 · Cited by 3,801 · see citing works
Identification of influential spreaders in complex networks
Kitsak, M., Gallos, L. K., Havlin, S., Liljeros, F., Muchnik, L., Stanley, E., & Makse, H. A. (2010) · Nature Physics · doi:10.1038/nphys1746 · Cited by 3,224 · see citing works
The spreading of misinformation online
Del Vicario, M., Bessi, A., Zollo, F., Petroni, F., Scala, A., Caldarelli, G., Stanley, H. E., & Quattrociocchi, W. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1517441113 · Cited by 2,407 · see citing works
Why civil resistance works: the strategic logic of nonviolent conflict
Stephan, M. J., & Chenoweth, E. (2012) · Choice Reviews Online · doi:10.5860/choice.49-4127 · Cited by 2,169 · see citing works
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 · see citing works
Networks beyond pairwise interactions: Structure and dynamics
Battiston, F., Cencetti, G., Iacopini, I., Latora, V., Lucas, M., Patania, A., Young, J.-G., & Petri, G. (2020) · Physics Reports · doi:10.1016/j.physrep.2020.05.004 · Cited by 1,739 · see citing works
Self-citationThe Concept of Social Movement
Diani, M. (1992) · The Sociological Review · doi:10.1111/j.1467-954x.1992.tb02943.x · Cited by 1,416 · see citing works
Networks beyond pairwise interactions: Structure and dynamics
Battiston, F., Cencetti, G., Iacopini, I., Latora, V., Lucas, M., Patania, A., Young, J., & Petri, G. (2020) · UCL Discovery (University College London) · Cited by 1,179 · see citing works
Self-citationThe physics of higher-order interactions in complex systems
Battiston, F., Amico, E., Barrat, A., Bianconi, G., de Arruda, G. F., Franceschiello, B., Iacopini, I., Kéfi, S., Latora, V., Moreno, Y., et al. (2021) · Nature Physics · doi:10.1038/s41567-021-01371-4 · Cited by 954 · see citing works
Self-citationFrom a Small to a Large Minority: Women in Scandinavian Politics
Dahlerup, D. (1988) · Scandinavian Political Studies · doi:10.1111/j.1467-9477.1988.tb00372.x · Cited by 903 · see citing works
Simplicial models of social contagion
Iacopini, I., Petri, G., Barrat, A., & Latora, V. (2019) · Nature Communications · doi:10.1038/s41467-019-10431-6 · Cited by 899 · see citing works
Self-citationHigh-Resolution Measurements of Face-to-Face Contact Patterns in a Primary School
Stehlé, J., Voirin, N., Barrat, A., Cattuto, C., Isella, L., Pinton, J.-F., Quaggiotto, M., den Broeck, W. V., Régis, C., Lina, B., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023176 · Cited by 834 · see citing works
Self-citationWhat's in a crowd? Analysis of face-to-face behavioral networks
Isella, L., Stehlé, J., Barrat, A., Cattuto, C., Pinton, J.-F., & den Broeck, W. V. (2010) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2010.11.033 · Cited by 823 · see citing works
Self-citationThe Critical Mass in Collective Action.
Macy, M. W., Marwell, G., & Oliver, P. E. (1994) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2074274 · Cited by 818 · see citing works
Hypergraphs - Combinatorics of Finite Sets
(1989) · North-Holland mathematical library · doi:10.1016/s0924-6509(08)x7007-2 · Cited by 792 · see citing works
Nyborg, K., Anderies, J. M., Dannenberg, A., Lindahl, T., Schill, C., Schlüter, M., Adger, W. N., Arrow, K. J., Barrett, S., Carpenter, S., et al. (2016) · Science · doi:10.1126/science.aaf8317 · Cited by 775 · see citing works
Experimental evidence for tipping points in social convention
Centola, D., Becker, J., Brackbill, D., & Baronchelli, A. (2018) · Science · doi:10.1126/science.aas8827 · Cited by 750 · see citing works
Self-citationParanjape, A., Benson, A. R., & Leskovec, J. (2017) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3018661.3018731 · Cited by 726 · see citing works
Modelling dynamical processes in complex socio-technical systems
Vespignani, A. (2011) · Nature Physics · doi:10.1038/nphys2160 · Cited by 649 · see citing works
Evolutionary dynamics of higher-order interactions in social networks
Alvarez-Rodriguez, U., Battiston, F., de Arruda, G. F., Moreno, Y., Perc, M., & Latora, V. (2021) · Nature Human Behaviour · doi:10.1038/s41562-020-01024-1 · Cited by 593 · see citing works
Mastrandrea, R., Fournet, J., & Barrat, A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0136497 · Cited by 590 · see citing works
Self-citationThe Paradox of Group Size in Collective Action: A Theory of the Critical Mass. II.
Oliver, P. E., & Marwell, G. (1988) · American Sociological Review · doi:10.2307/2095728 · Cited by 554 · see citing works
Simplicial closure and higher-order link prediction
Benson, A. R., Abebe, R., Schaub, M. T., Jadbabaie, A., & Kleinberg, J. M. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1800683115 · Cited by 548 · see citing works
From networks to optimal higher-order models of complex systems
Lambiotte, R., Rosvall, M., & Scholtes, I. (2019) · Nature Physics · doi:10.1038/s41567-019-0459-y · Cited by 487 · see citing works
What are higher-order networks?
Bick, C., Gross, E., Harrington, H. A., & Schaub, M. T. (2023) · SIAM Review · doi:10.1137/21m1414024 · Cited by 420 · see citing works
Social consensus through the influence of committed minorities
Xie, J., Sreenivasan, S., Korniss, G., Zhang, W., Lim, C., & Szymanski, B. K. (2011) · Physical Review E · doi:10.1103/physreve.84.011130 · Cited by 416 · see citing works
Sharp transition towards shared vocabularies in multi-agent systems
Baronchelli, A., Felici, M., Loreto, V., Caglioti, E., & Steels, L. (2006) · Journal of Statistical Mechanics: Theory and Experiment · doi:10.1088/1742-5468/2006/06/p06014 · Cited by 402 · see citing works
Self-citationEvolutionary dynamics of higher-order interactions in social networks
Alvarez-Rodriguez, U., Battiston, F., de Arruda, G. F., Moreno, Y., Perc, M., & Latora, V. (2021) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-214990 · Cited by 402 · see citing works
The Critical Periphery in the Growth of Social Protests
Barberá, P., Wang, N., Bonneau, R., Jost, J. T., Nagler, J., Tucker, J., & González-Bailón, S. (2015) · PLOS ONE · doi:10.1371/journal.pone.0143611 · Cited by 348 · see citing works
Legislative cosponsorship networks in the US House and Senate
Fowler, J. H. (2005) · Social Networks · doi:10.1016/j.socnet.2005.11.003 · Cited by 335 · see citing works
The role of inflexible minorities in the breaking of democratic opinion dynamics
Galam, S., & Jacobs, F. (2007) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2007.03.034 · Cited by 313 · see citing works
The Why, How, and When of Representations for Complex Systems
Torres, L., Blevins, A. S., Bassett, D. S., & Eliassi‐Rad, T. (2021) · SIAM Review · doi:10.1137/20m1355896 · Cited by 308 · see citing works
Evidence of complex contagion of information in social media: An experiment using Twitter bots
Mønsted, B., Sapiezynski, P., Ferrara, E., & Lehmann, S. (2017) · PLoS ONE · doi:10.1371/journal.pone.0184148 · Cited by 302 · see citing works
Some Effects of Proportions on Group Life
Kanter, R. M. (1977) · Springer eBooks · doi:10.1007/978-1-4684-4754-5_5 · Cited by 285 · see citing works
The spontaneous emergence of conventions: An experimental study of cultural evolution
Centola, D., & Baronchelli, A. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1418838112 · Cited by 282 · see citing works
Self-citationMathematical structure in human affairs
Atkin, R. H. (1974) · Cited by 279 · see citing works
Patania, A., Petri, G., & Vaccarino, F. (2017) · EPJ Data Science · doi:10.1140/epjds/s13688-017-0114-8 · Cited by 254 · see citing works
Self-citationSen, P., & Chakrabarti, B. K. (2014) · CERN Document Server (European Organization for Nuclear Research) · Cited by 252 · see citing works
Sensitive intervention points in the post-carbon transition
Farmer, J. D., Hepburn, C., Ives, M. C., Hale, T., Wetzer, T., Mealy, P., Rafaty, R., Srivastav, S., & Way, R. (2019) · Science · doi:10.1126/science.aaw7287 · Cited by 248 · see citing works
Génois, M., Vestergaard, C. L., Fournet, J., Panisson, A., BONMARIN, I., & Barrat, A. (2015) · Network Science · doi:10.1017/nws.2015.10 · Cited by 225 · see citing works
Self-citationCourtney, O. T., & Ginestra Bianconi, A. (2016) · Physical review. E · doi:10.1103/physreve.93.062311 · Cited by 217 · see citing works
Nonequilibrium dynamics of language games on complex networks
Dall’Asta, L., Baronchelli, A., Barrat, A., & Loreto, V. (2006) · Physical Review E · doi:10.1103/physreve.74.036105 · Cited by 199 · see citing works
Self-citationCentola, D. (2013) · Rationality and Society · doi:10.1177/1043463112473734 · Cited by 171 · see citing works
Simplicial Activity Driven Model
Petri, G., & Barrat, A. (2018) · Physical Review Letters · doi:10.1103/physrevlett.121.228301 · Cited by 170 · see citing works
Self-citationTemporal properties of higher-order interactions in social networks
Cencetti, G., Battiston, F., Lepri, B., & Karsai, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-86469-8 · Cited by 165 · see citing works
The emergence of consensus: a primer
Baronchelli, A. (2018) · Royal Society Open Science · doi:10.1098/rsos.172189 · Cited by 161 · see citing works
Self-citationMultibody interactions and nonlinear consensus dynamics on networked systems
Neuhäuser, L., Mellor, A., & Lambiotte, R. (2020) · Physical review. E · doi:10.1103/physreve.101.032310 · Cited by 160 · see citing works
Nonequilibrium phase transition in negotiation dynamics
Baronchelli, A., Dall’Asta, L., Barrat, A., & Loreto, V. (2007) · Physical Review E · doi:10.1103/physreve.76.051102 · Cited by 114 · see citing works
Self-citationCOVID-19 Vaccine Hesitancy: Shortening the Last Mile
Chevallier, C., Hacquin, A.-S., & Mercier, H. (2021) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2021.02.002 · Cited by 113 · see citing works
Behavioral dynamics and influence in networked coloring and consensus
Judd, S. J., Kearns, M. J., & Vorobeychik, Y. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1001280107 · Cited by 101 · see citing works
Simplicial contagion in temporal higher-order networks
Chowdhary, S., Kumar, A., Cencetti, G., Iacopini, I., & Battiston, F. (2021) · Journal of Physics Complexity · doi:10.1088/2632-072x/ac12bd · Cited by 99 · see citing works
Self-citationInfluential groups for seeding and sustaining nonlinear contagion in heterogeneous hypergraphs
St-Onge, G., Iacopini, I., Latora, V., Barrat, A., Petri, G., Allard, A., & Hébert‐Dufresne, L. (2022) · Communications Physics · doi:10.1038/s42005-021-00788-w · Cited by 95 · see citing works
Self-citationAdaptive voter model on simplicial complexes
Horstmeyer, L., & Kuehn, C. (2020) · Physical review. E · doi:10.1103/physreve.101.022305 · Cited by 94 · see citing works
Phase transitions in information spreading on structured populations
Davis, J. T., Perra, N., Zhang, Q., Moreno, Y., & Vespignani, A. (2020) · Nature Physics · doi:10.1038/s41567-020-0810-3 · Cited by 92 · see citing works
Humans display a reduced set of consistent behavioral phenotypes in dyadic games
Poncela-Casasnovas, J., Gutiérrez-Roig, M., Gracia-Lázaro, C., Vicens, J., Gómez‐Gardeñes, J., Perelló, J., Moreno, Y., Duch, J., & Sánchez, Á. (2016) · Science Advances · doi:10.1126/sciadv.1600451 · Cited by 83 · see citing works
Enhancement of dominant attitudes in group discussion.
Myers, D. G., & Bishop, G. D. (1971) · Journal of Personality and Social Psychology · doi:10.1037/h0031920 · Cited by 81 · see citing works
Evolution of Opinions on Social Networks in the Presence of Competing Committed Groups
Xie, J., Emenheiser, J., Kirby, M., Sreenivasan, S., Szymanski, B. K., & Korniss, G. (2012) · PLoS ONE · doi:10.1371/journal.pone.0033215 · Cited by 78 · see citing works
Evolutionary games on simplicial complexes
Guo, H., Jia, D., Sendiña–Nadal, I., Zhang, M., Wang, Z., Li, X., Alfaro-Bittner, K., Moreno, Y., & Boccaletti, S. (2021) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2021.111103 · Cited by 77 · see citing works
The Great Illusion: Ignorance, Informational Cascades, and the Persistence of Unpopular Norms
Bicchieri, C., & Fukui, Y. (1999) · Business Ethics Quarterly · doi:10.2307/3857639 · Cited by 74 · see citing works
Strength of social influence in trust networks in product review sites
Yeung, C. A., & Iwata, T. (2011) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/1935826.1935899 · Cited by 71 · see citing works
Q-analysis and the structure of friendship networks
Freeman, L. C. (1980) · International Journal of Man-Machine Studies · doi:10.1016/s0020-7373(80)80021-6 · Cited by 69 · see citing works
The dynamics of norm change in the cultural evolution of language
Amato, R., Lacasa, L., Díaz-Guilera, A., & Baronchelli, A. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1721059115 · Cited by 62 · see citing works
Self-citationThe Gender Gap in Psychotherapy
Rieker, P. P., & Carmen, E. (. (1984) · Springer eBooks · doi:10.1007/978-1-4684-4754-5 · Cited by 61 · see citing works
Predicting emerging social conventions in online social networks
Kooti, F., Mason, W., Gummadi, K. P., & Cha, M. (2012) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2396761.2396820 · Cited by 55 · see citing works
A Bounded-Confidence Model of Opinion Dynamics on Hypergraphs
Hickok, A., Kureh, Y. H., Brooks, H. Z., Feng, M., & Porter, M. A. (2022) · SIAM Journal on Applied Dynamical Systems · doi:10.1137/21m1399427 · Cited by 55 · see citing works
Constructing social systems through computer-mediated communication
Becker, B., & Mark, G. (1999) · Virtual Reality · doi:10.1007/bf01434995 · Cited by 47 · see citing works
Committed activists and the reshaping of status-quo social consensus
Mistry, D., Zhang, Q., Perra, N., & Baronchelli, A. (2015) · Physical Review E · doi:10.1103/physreve.92.042805 · Cited by 44 · see citing works
Self-citationEmerging Frontiers in Nonlinear Science
Kevrekidis, P. G., Cuevas–Maraver, J., & Saxena, A. (2020) · Nonlinear systems and complexity · doi:10.1007/978-3-030-44992-6 · Cited by 44 · see citing works
Nonlinearity + Networks: A 2020 Vision
Porter, M. A. (2020) · Nonlinear systems and complexity · doi:10.1007/978-3-030-44992-6_6 · Cited by 41 · see citing works
Dynamics of majority rule on hypergraphs
Noonan, J., & Lambiotte, R. (2021) · Physical review. E · doi:10.1103/physreve.104.024316 · Cited by 35 · see citing works
Critical mass effect in evolutionary games triggered by zealots
Cardillo, A., & Masuda, N. (2020) · Physical Review Research · doi:10.1103/physrevresearch.2.023305 · Cited by 32 · see citing works
Modeling the Forming of Public Opinion: An approach from Sociophysics
Galam, S. (2013) · Global Economics and Management Review · doi:10.1016/s2340-1540(13)70002-1 · Cited by 31 · see citing works
Analytic treatment of tipping points for social consensus in large random networks
Zhang, W., Lim, C., & Szymanski, B. K. (2012) · Physical Review E · doi:10.1103/physreve.86.061134 · Cited by 24 · see citing works
The impact of incorrect social information on collective wisdom in human groups
Jayles, B., Escobedo, R., Cezera, S., Blanchet, A., Kameda, T., Sire, C., & Guy Theraulaz, A. (2020) · Journal of The Royal Society Interface · doi:10.1098/rsif.2020.0496 · Cited by 22 · see citing works
Propensity and stickiness in the naming game: Tipping fractions of minorities
Thompson, A. M., Szymanski, B. K., & Lim, C. C. (2014) · Physical Review E · doi:10.1103/physreve.90.042809 · Cited by 20 · see citing works
Higher-order Network Analysis Takes Off, Fueled by Classical Ideas and New DataPreprint
Benson, A. R., Gleich, D. F., & Higham, D. J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.05031 · Cited by 19 · see citing works
Analysis of the high-dimensional naming game with committed minorities
Pickering, W., Szymanski, B. K., & Lim, C. C. (2016) · Physical review. E · doi:10.1103/physreve.93.052311 · Cited by 16 · see citing works
Understanding drivers when investing for impact: an experimental study
Amicis, L. D., Binenti, S., Cardoso, F. M., Gracia-Lázaro, C., Sánchez, Á., & Moreno, Y. (2020) · Humanities and Social Sciences Communications · doi:10.1057/s41599-020-0447-y · Cited by 16 · see citing works
Iten, A., Bonfillon, C., Bouvard, T., Siegrist, C., & Pittet, D. (2013) · Antimicrobial Resistance and Infection Control · doi:10.1186/2047-2994-2-s1-p37 · Cited by 10 · see citing works
Effects of communication burstiness on consensus formation and tipping points in social dynamics
Doyle, C., Szymanski, B. K., & Korniss, G. (2017) · Physical review. E · doi:10.1103/physreve.95.062303 · Cited by 10 · see citing works
Consensus dynamics on temporal hypergraphs
Neuhäuser, L., Lambiotte, R., & Schaub, M. T. (2021) · Physical review. E · doi:10.1103/physreve.104.064305
Flagged first, then by citations
3 of the 90 references couldn’t be matched to a known paper.
Research works printed but not linked: 4
- Grey, S. Numbers and beyond: the relevance of critical mass in gender research. Politics Gend. 2, 492 (2006).
- Kelley, H. H. & Lamb, T. W. Certainty of judgment and resistance to social influence. J. Abnorm. Psychol. 55, 137 (1957).
- Jenness, A. The role of discussion in changing opinion regarding a matter of fact. J. Abnorm. Psychol. 27, 279 (1932).
- Kooti, F., Yang, H., Cha, M., Gummadi, K. & Mason, W. The emergence of conventions in online social networks. In Proceedings of the International AAAI Conference on Web and Social Media, vol. 6 (2012).
Cited by
Sorted by citations
The structure and dynamics of networks with higher order interactions
Boccaletti, S., Lellis, P. D., del Genio, C. I., Alfaro-Bittner, K., Criado, R., Jalan, S., & Romance, M. (2023) · Physics Reports · doi:10.1016/j.physrep.2023.04.002 · Cited by 379 · see citing works
A Survey on Hypergraph Representation Learning
Antelmi, A., Cordasco, G., Polato, M., Scarano, V., Spagnuolo, C., & Yang, D. (2023) · ACM Computing Surveys · doi:10.1145/3605776 · Cited by 230 · see citing works
Contagion dynamics on higher-order networks
de Arruda, G. F., Aleta, A., & Moreno, Y. (2024) · Nature Reviews Physics · doi:10.1038/s42254-024-00733-0 · Cited by 109 · see citing works
Higher-order interactions shape collective human behaviour
Battiston, F., Capraro, V., Karimi, F., Lehmann, S., Migliano, A. B., Sadekar, O., Sánchez, Á., & Perc, M. (2025) · Nature Human Behaviour · doi:10.1038/s41562-025-02373-5 · Cited by 99 · see citing works
Influential groups for seeding and sustaining nonlinear contagion in heterogeneous hypergraphs
St-Onge, G., Iacopini, I., Latora, V., Barrat, A., Petri, G., Allard, A., & Hébert‐Dufresne, L. (2022) · Communications Physics · doi:10.1038/s42005-021-00788-w · Cited by 95 · see citing works
Self-citationThe temporal dynamics of group interactions in higher-order social networks
Iacopini, I., Karsai, M., & Barrat, A. (2024) · Nature Communications · doi:10.1038/s41467-024-50918-5 · Cited by 90 · see citing works
Self-citationMultistability, intermittency, and hybrid transitions in social contagion models on hypergraphs
de Arruda, G. F., Petri, G., Rodriguez, P. M., & Moreno, Y. (2023) · Nature Communications · doi:10.1038/s41467-023-37118-3 · Cited by 86 · see citing works
Self-citationEmergent social conventions and collective bias in LLM populations
Ashery, A. F., Aiello, L. M., & Baronchelli, A. (2025) · Science Advances · doi:10.1126/sciadv.adu9368 · Cited by 81 · see citing works
Self-citationHigher-order temporal interactions promote the cooperation in the multiplayer snowdrift game
Xu, Y. L., Wang, J., Xia, C., & Wang, Z. (2023) · Science China Information Sciences · doi:10.1007/s11432-022-3738-3 · Cited by 67 · see citing works
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide
Kim, S., Lee, S. Y., Gao, Y., Antelmi, A., Polato, M., & Shin, K. (2024) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3637528.3671457 · Cited by 72 · see citing works
A system model of three-body interactions in complex networks: consensus and conservation
Shang, Y. (2022) · Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rspa.2021.0564 · Cited by 50 · see citing works
Hyper-cores promote localization and efficient seeding in higher-order processes
Mancastroppa, M., Iacopini, I., Petri, G., & Barrat, A. (2023) · Nature Communications · doi:10.1038/s41467-023-41887-2 · Cited by 51 · see citing works
Self-citationDrivers of social influence in the Twitter migration to Mastodon
Cava, L. L., Aiello, L. M., & Tagarelli, A. (2023) · Scientific Reports · doi:10.1038/s41598-023-48200-7 · Cited by 48 · see citing works
A simplicial epidemic model for COVID-19 spread analysis
Chen, Y., Gel, Y. R., MARATHE, M. V., & Poor, H. V. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2313171120 · Cited by 39 · see citing works
Baronchelli, A. (2024) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2023.0028 · Cited by 29 · see citing works
Self-citationCapturing complex interactions in disease ecology with simplicial sets
Silk, M. J., Wilber, M. Q., & Fefferman, N. H. (2022) · Ecology Letters · doi:10.1111/ele.14079 · Cited by 25 · see citing works
Sensitive intervention points: a strategic approach to climate action
Mealy, P., Barbrook-Johnson, P., Ives, M. C., Srivastav, S., & Hepburn, C. J. (2023) · Oxford Review of Economic Policy · doi:10.1093/oxrep/grad043 · Cited by 29 · see citing works
A unified framework for simplicial Kuramoto models
Nurisso, M., Arnaudon, A., Lucas, M., Peach, R. L., Expert, P., Vaccarino, F., & Petri, G. (2024) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0169388 · Cited by 23 · see citing works
Self-citationConceptual representations of animal social networks: an overview
Silk, M. J. (2023) · Animal Behaviour · doi:10.1016/j.anbehav.2023.04.017 · Cited by 17 · see citing works
Cooperation dynamics on hypergraphs with punishment and Q-learning
Zou, K., & Huang, C. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128989 · Cited by 13 · see citing works
Insights from exact social contagion dynamics on networks with higher-order structures
Kiss, I. Z., Iacopini, I., Šimon, P., & Georgiou, N. (2023) · Journal of Complex Networks · doi:10.1093/comnet/cnad044 · Cited by 14 · see citing works
Self-citationHow sustainable is OpenStreetMap? Tracking individual trajectories of editing behavior
Zhang, X., An, J., Zhou, Y., Yang, M. J., & Zhao, X. (2024) · International Journal of Digital Earth · doi:10.1080/17538947.2024.2311320 · Cited by 13 · see citing works
The structural evolution of temporal hypergraphs through the lens of hyper-cores
Mancastroppa, M., Iacopini, I., Petri, G., & Barrat, A. (2024) · EPJ Data Science · doi:10.1140/epjds/s13688-024-00490-1 · Cited by 13 · see citing works
Self-citationCooperation without punishment
Battu, B., & Rahwan, T. (2023) · Scientific Reports · doi:10.1038/s41598-023-28372-y · Cited by 12 · see citing works
Chen, K., Zhang, Y., Luo, M. J., & Zheng, X. (2025) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0248208 · Cited by 12 · see citing works
Susceptible-infected-recovered-susceptible processes competing on simplicial complexes
Zhao, L., Wang, H., Yang, H., Gu, C., & Moore, J. M. (2024) · Physical review. E · doi:10.1103/physreve.110.064311 · Cited by 10 · see citing works
The Pareto effect in tipping social networks: from minority to majority
Everall, J. P., Tschofenig, F., Donges, J., & Otto, I. M. (2025) · Earth System Dynamics · doi:10.5194/esd-16-189-2025 · Cited by 17 · see citing works
Entropy-based models to randomise real-world hypergraphs
Saracco, F., Petri, G., Lambiotte, R., & Squartini, T. (2025) · Communications Physics · doi:10.1038/s42005-025-02182-2 · Cited by 13 · see citing works
Self-citationPichon, M., Carter, D. J., Howard‐Merrill, L., Sono, R., Gimunta, V., Rutenge, O., Thiaw, Y., Stoebenau, K., Perrin, N., & Buller, A. M. (2022) · Frontiers in Reproductive Health · doi:10.3389/frph.2022.1000853 · Cited by 10 · see citing works
Discovering network dynamics with neural symbolic regression
Yu, Z., Ding, J., & Li, Y. (2025) · Nature Computational Science · doi:10.1038/s43588-025-00893-8 · Cited by 8 · see citing works
Effect of individual activity level heterogeneity on disease spreading in higher-order networks
Li, M., Huo, L., Xie, X., & Dong, Y. (2024) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0207855 · Cited by 6 · see citing works
Silk, M. J., & Giménez, O. (2023) · Ecology and Evolution · doi:10.1002/ece3.9871 · Cited by 6 · see citing works
Group adaptation drives opinion dynamics in higher-order networks
Agostinelli, C., Mancastroppa, M., & Barrat, A. (2026) · APS Open Science · doi:10.1103/gcz4-wwb3 · Cited by 4 · see citing works
Self-citationFragmentation from group interactions: A higher-order adaptive voter model
Papanikolaou, N., Lambiotte, R., & Vaccario, G. (2023) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2023.129257 · Cited by 4 · see citing works
Negative public opinion and minority-driven social change in hypergraphs
Gong, L., Huang, C., & Jiang, L.-L. (2025) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0257900 · Cited by 4 · see citing works
Zhao, D., Luo, J., Zhang, B., Qian, C., Zhong, M. J., Li, S., Han, J., Peng, H., & Wang, W. (2026) · Chaos An Interdisciplinary Journal of Nonlinear Science · doi:10.1063/5.0300040 · Cited by 3 · see citing works
Strategy evolution on temporal hypergraphs
Wang, X., Zhou, L., McAvoy, A., Tian, Z., & Li, A. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2516380123 · Cited by 5 · see citing works
Kanze, D., & Piazza, A. (2025) · Organization Science · doi:10.1287/orsc.2025.20141 · Cited by 3 · see citing works
Howard‐Merrill, L., Pichon, M., Witt, A., Sono, R., Gimunta, V., Hofer, E., Kiluvia, F., Alfred, M., Yohanna, E., & Buller, A. M. (2024) · BMC Public Health · doi:10.1186/s12889-024-20440-w · Cited by 3 · see citing works
Beyond Pairwise Network Interactions: Implications for Information Centrality
Lera, S. C., & Leng, Y. (2025) · Information Systems Research · doi:10.1287/isre.2024.1097 · Cited by 2 · see citing works
Adaptive behaviors neutralize bistable explosive transitions in higher-order contagion
Mancastroppa, M., Karsai, M., & Barrat, A. (2026) · APS Open Science · doi:10.1103/1sgn-k3fk · Cited by 2 · see citing works
Self-citationA Political Radicalization Framework Based on Moral Foundations Theory
Interian, R. (2024) · Mathematics · doi:10.3390/math12132121 · Cited by 2 · see citing works
Essilfie-Quaye, S., Reddy, P. S., Adeturinmo, M., Lloyd, C. M., & Morgan, W. (2025) · Wellcome Open Research · doi:10.12688/wellcomeopenres.24584.1 · Cited by 1 · see citing works
A typology of rules for knowledge exchange in higher-order interactions
Sisk, A., Silk, M. J., Williams, N. D., & Fefferman, N. H. (2026) · PLOS complex systems. · doi:10.1371/journal.pcsy.0000080 · Cited by 1 · see citing works
Symmetry breaking in collective decision-making through higher-order interactions
March-Pons, D., Pastor‐Satorras, R., & Miguel, M. C. (2026) · npj Complexity · doi:10.1038/s44260-026-00071-5 · Cited by 1 · see citing works
How Does Reverse‐Conformity Ambivalent Psychology Influence Rumor Spreading?
Zhang, J., Su, Y., Yan, Z., & Zhang, Y. (2026) · Discrete Dynamics in Nature and Society · doi:10.1155/ddns/8559363 · Cited by 1 · see citing works
Unraveling the emergence of collective behavior in networks of cognitive agents
Zomer, N., & Domenico, M. D. (2026) · npj Artificial Intelligence · doi:10.1038/s44387-026-00091-5 · Cited by 1 · see citing works
Opinion response functions are key to understanding the tipping of social conventions
Wyse, S. K., & Foxall, E. (2024) · Journal of Statistical Mechanics Theory and Experiment · doi:10.1088/1742-5468/ad86b6 · Cited by 1 · see citing works
A brief history of a subversive future: cities of ecological entanglement
Stange, L. L. (2025) · Global Social Challenges Journal · doi:10.1332/27523349y2025d000000047 · Cited by 1 · see citing works
Beyond Pairwise Network Interactions: Implications for Information CentralityPreprint
Lera, S. C., & Leng, Y. (2024) · SSRN Electronic Journal · doi:10.2139/ssrn.4708802
Resisting harmful social norms change using social inoculation
Lahiri, S. (2024) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2024.101914
Iron and steel workers acquiring a factory in exchange for a single coin: a genuine people’s sector
Ergün, Ü. R. (2024) · Labor History · doi:10.1080/0023656x.2024.2419651
Vorster, J. S., & Leenen, L. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-77603-8_3
Ma, J., & Yuan, Z. (2025) · Physics Letters A · doi:10.1016/j.physleta.2025.130582
Orgel, J. P. R. O., Madhurapantula, R. S., Jagannathan, N., & Moller, A. C. (2025) · Journal of Leadership Education · doi:10.1108/jole-01-2025-0012
Innovation-exnovation dynamics on trees and trusses
Lee, E., & Ortega, E. (2025) · Physical Review Research · doi:10.1103/ynwt-7g91
Community aware temporal network generation
Girardini, N. A., Longa, A., Trebucchi, G., Cencetti, G., Passerini, A., & Lepri, B. (2025) · Applied Network Science · doi:10.1007/s41109-025-00731-w
The Effect of Artifacts on Consensus Formation: An Agent-Based Simulation Approach
Vorster, J. S., & Leenen, L. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-032-04777-9_7
Co-evolution of groups and opinions in an agent-based model
Cassells, D., Vendeville, A., Tabourier, L., & Morales, P. R. (2025) · PLoS ONE · doi:10.1371/journal.pone.0338486 · Cited by 1 · see citing works
Mancastroppa, M., Iacopini, I., Petri, G., & Barrat, A. (2024) · Figshare · doi:10.6084/m9.figshare.26378026
Self-citationStructure, influence, and consensus: Modeling majority-driven dynamics on hypernetworks
Lu, J., Li, G., & He, X. (2026) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2026.117906
HyperSearch: Prediction of New Hyperedges Through Unconstrained yet Efficient Search
Choo, H., Bu, F., Hwang, H., Yoon, Y., & Shin, K. (2025) · Proceedings · doi:10.1109/icdm65498.2025.00025
Cross-order induced behaviors in contagion dynamics on higher-order networks
Danovski, K., Meloni, S., & Starnini, M. (2026) · Physical Review Research · doi:10.1103/pngx-s5xx
Left-wing inertia toward animal advocacy: A research blind spot
Veitch, P. C., & Gregson, R. (2026) · Psychology of Human-Animal Intergroup Relations · doi:10.5964/phair.22271
Multilayer contagions in animal groups
Silk, M., & Fefferman, N. H. (2026) · Animal Behaviour · doi:10.1016/j.anbehav.2026.123525
Yi, W., & Wu, W. (2026) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2026.113179
Hypergraph Evolutionary Public Goods Game Network Modeling Method Based on Prospect Theory
Wang, D. (2026) · International Conference on Innovation Management and Information Systems (ICIMIS) · doi:10.1145/3821966.3822007
Gwak, D., Park, J., Kim, S., & Jung, J. (2026) · IEEE Access · doi:10.1109/access.2026.3740904
Heterogeneous higher-order interactions govern collective opinion dynamics
Hu, Y., Yu, D., Wang, X., Li, T.-Y., Li, X.-N., Jia, Y., & Yang, L.-J. (2026) · Nonlinear Dynamics · doi:10.1007/s11071-026-13130-2
- Authors
- Iacopini, I., Petri, G., Baronchelli, A., & Barrat, A.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Institute for Scientific Interchange (IT)
- University of London (GB)
- Tokyo Institute of Technology (JP)
- Venue
- Communications Physics
- Published
- 2022-03-18
- Volume
- 5
- Issue
- 1
- Pages
- 64
- ISSN
- 2399-3650 (ISSN-L)
- OpenAlex
- W3210401123
- Cited by
- 69
- References
- 90
- Citations by year
- 2026: 16 · 2025: 19 · 2024: 17 · 2023: 13 · 2022: 4
- FWCI
- 5.00
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Communications Physics (publishedVersion, cc-by)
- City Research Online (City University London) (acceptedVersion)
- arXiv (Cornell University) (submittedVersion)
- HAL (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- Agence Nationale de la Recherche (ANR-19-CE46-0008)
- James S. McDonnell Foundation
- Intesa SanPaolo Innovation center
- MEXT | Japan Society for the Promotion of Science (20H04288)
- 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 › Economics, Econometrics and Finance › Economics and Econometrics › Complex Systems and Time Series Analysis
- Keywords
- critical mass, social conventions, social norms, minority influence, tipping points, group interaction, higher-order networks, behavior change, group size
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