Resilience denotes the capacity of a system to withstand shocks and its ability to recover from them. We develop a framework to quantify the resilience of highly volatile, non-equilibrium social organizations, such as collectives or collaborating teams. It consists of four steps: (i) delimitation, i.e. narrowing down the target systems, (ii) conceptualization, i.e. identifying how to approach social organizations, (iii) formal representation using a combination of agent-based and network models, (iv) operationalization, i.e. specifying measures and demonstrating how they enter the calculation of resilience. Our framework quantifies two dimensions of resilience, the robustness of social organizations and their adaptivity, and combines them in a novel resilience measure. It allows monitoring resilience instantaneously using longitudinal data instead of an ex-post evaluation.

Keywords:

References

1. Abercrombie, G. and Batista-Navarro, R. , Sentiment and position-taking analysis of parliamentary debates: A systematic literature review, J. Comput. Soc. Sci. 3 (2020) 245–270. Crossref, Google Scholar
2. Adger, W. N. , Social and ecological resilience: Are they related? Prog. Human Geography 24 (2000) 347–364. Crossref, Web of Science, Google Scholar
3. de Aguiar, M. A. M. and Bar-Yam, Y. , Spectral analysis and the dynamic response of complex networks, Phys. Rev. E 71 (2005) 016106. Crossref, Web of Science, Google Scholar
4. Albert, R., Albert, I. and Nakarado, G. L. , Structural vulnerability of the North American power grid, Phys. Rev. E 69 (2004) 025103. Crossref, Web of Science, Google Scholar
5. Andres, G., Casiraghi, G., Vaccario, G. and Schweitzer, F., Reconstructing signed relations from interaction data, arXiv:2209.03219. Google Scholar
6. Annarelli, A. and Nonino, F. , Strategic and operational management of organizational resilience: Current state of research and future directions, Omega 62 (2016) 1–18. Crossref, Web of Science, Google Scholar
7. Arnetz, B. B., Nevedal, D. C., Lumley, M. A., Backman, L. and Lublin, A. , Trauma resilience training for police: Psychophysiological and performance effects, J. Police Crim. Psychol. 24 (2009) 1–9. Crossref, Google Scholar
8. Ash, J. and Newth, D. , Optimizing complex networks for resilience against cascading failure, Physica A 380 (2007) 673–683. Crossref, Web of Science, Google Scholar
9. Baggio, J. A., Brown, K. and Hellebrandt, D. , Boundary object or bridging concept? A citation network analysis of resilience, Ecol. Soc. 20 (2015) 2. Crossref, Web of Science, Google Scholar
10. Bagrow, J. P., Lehmann, S. and Ahn, Y.-Y. , Robustness and modular structure in networks, Netw. Sci. 3 (2015) 509–525. Crossref, Google Scholar
11. Barlow, J., França, F., Gardner, T. A., Hicks, C. C., Lennox, G. D., Berenguer, E., Castello, L., Economo, E. P., Ferreira, J., Guénard, B., Gontijo Leal, C., Isaac, V., Lees, A. C., Parr, C. L., Wilson, S. K., Young, P. J. and Graham, N. A. J. , The future of hyperdiverse tropical ecosystems, Nature 559 (2018) 517–526. Crossref, Web of Science, Google Scholar
12. Bascompte, J. and Jordano, P. , Plant-animal mutualistic networks: The architecture of biodiversity, Annu. Rev. Ecol. Evolut. System. 38 (2007) 567–593. Crossref, Web of Science, Google Scholar
13. Battiston, F. et al., The physics of higher-order interactions in complex systems, Nat. Phys. 17 (2021) 1093–1098. Crossref, Web of Science, Google Scholar
14. Beyerlein, M. M., Freedman, S., McGee, C., Moran, L. and Beyerlein, M. , Beyond Teams: Building the Collaborative Organization (Jossey-Bass/Pfeiffer, 2003). Google Scholar
15. Biggs, R. , et al., Toward principles for enhancing the resilience of ecosystem services, Annu. Rev. Environ. Resourc. 37 (2012) 421–448. Crossref, Web of Science, Google Scholar
16. Bonacich, P. , Power and centrality: A family of measures, Amer. J. Sociol. 92 (1987) 1170–1182. Crossref, Web of Science, Google Scholar
17. Brandenberger, L., Casiraghi, G., Nanumyan, V. and Schweitzer, F. , Quantifying triadic closure in multi-edge social networks, in International Conference on Advances in Social Networks Analysis and Mining (ACM, 2019), pp. 307–310. Crossref, Google Scholar
18. Brummitt, C. D., D’Souza, R. M. and Leicht, E. A. , Suppressing cascades of load in interdependent networks, Proc. Natl. Acad. Sci. 109 (2012) E680–E689. Crossref, Web of Science, Google Scholar
19. Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O’Rourke, T. D., Reinhorn, A. M., Shinozuka, M., Tierney, K., Wallace, W. A. and von Winterfeldt, D. , A framework to quantitatively assess and enhance the seismic resilience of communities, Earthq. Spectra 19 (2003) 733–752. Crossref, Web of Science, Google Scholar
20. Bruneau, M. and Reinhorn, A. , Exploring the concept of seismic resilience for acute care facilities, Earthq. Spectra 23 (2007) 41–62. Crossref, Web of Science, Google Scholar
21. Buldyrev, S. V., Parshani, R., Paul, G., Stanley, H. E. and Havlin, S. , Catastrophic cascade of failures in interdependent networks, Nature 464 (2010) 1025–1028. Crossref, Web of Science, Google Scholar
22. Burkholz, R., Garas, A. and Schweitzer, F. , How damage diversification can reduce systemic risk, Phys. Rev. E 93 (2016a) 42313. Crossref, Web of Science, Google Scholar
23. Burkholz, R., Leduc, M. V., Garas, A. and Schweitzer, F. , Systemic risk in multiplex networks with asymmetric coupling and threshold feedback, Physica D 323–324 (2016b) 64–72. Crossref, Web of Science, Google Scholar
24. Burkholz, R. and Schweitzer, F. , Framework for cascade size calculations on random networks, Phys. Rev. E 97 (2018) 042312. Crossref, Web of Science, Google Scholar
25. Carpenter, S., Walker, B., Anderies, J. M. and Abel, N. , From metaphor to measurement: Resilience of what to what? Ecosystems 4 (2001) 765–781. Crossref, Web of Science, Google Scholar
26. Casiraghi, G., Multiplex network regression: How do relations drive interactions? arXiv:2209.03219. Google Scholar
27. Casiraghi, G. , The block-constrained configuration model, Appl. Netw. Sci. 4 (2019) 123. Crossref, Google Scholar
28. Casiraghi, G. , The likelihood-ratio test for multi-edge network models, J. Phys.: Compl. 2 (2021) 035012. Crossref, Google Scholar
29. Casiraghi, G., Garas, A. and Schweitzer, F., Probing the robustness of nested multi-layer networks, arXiv:1911.03277. Google Scholar
30. Casiraghi, G. and Nanumyan, V. , Configuration models as an urn problem, Sci. Rept. 11 (2021) 13416. Crossref, Web of Science, Google Scholar
31. Casiraghi, G. and Nanumyan, V., ghypernet: Fit and simulate generalised hypergeometric ensembles of graphs, R package version 1.1.1.1. (2022) Google Scholar
32. Casiraghi, G., Nanumyan, V., Scholtes, I. and Schweitzer, F. , From relational data to graphs: Inferring significant links using generalized hypergeometric ensembles, in Social Informatics: 9th International Conference, Lecture Notes in Computer Science (Springer International Publishing, 2017), pp. 111–120. Crossref, Google Scholar
33. Casiraghi, G. and Schweitzer, F. , Improving the robustness of online social networks: A simulation approach of network interventions, Front. Robot. AI 7 (2020) 57. Crossref, Web of Science, Google Scholar
34. Casiraghi, G., Zingg, C. and Schweitzer, F. , The downside of heterogeneity: How established relations counteract systemic adaptivity in tasks assignments, Entropy 23 (2021) 1677. Crossref, Web of Science, Google Scholar
35. Chavez-Demoulin, V., Embrechts, P. and Hofert, M. , An extreme value approach for modeling operational risk losses depending on covariates, J. Risk Insur. 83 (2015) 735–776. Crossref, Web of Science, Google Scholar
36. Chiva, R., Alegre, J. and Lapiedra, R. , Measuring organisational learning capability among the workforce, Int. J. Manpower 28 (2007) 224–242. Crossref, Web of Science, Google Scholar
37. Cohen, R., Erez, K., Ben-Avraham, D. and Havlin, S. , Resilience of the internet to random breakdowns, Phys. Rev. Lett. 85 (2000) 4626. Crossref, Web of Science, Google Scholar
38. Coles, E. and Buckle, P. , Developing community resilience as a foundation for effective disaster recovery, Austral. J. Emerg. Manag. 19 (2004) 6–15. Google Scholar
39. Dakos, V., Carpenter, S. R., van Nes, E. H. and Scheffer, M. , Resilience indicators: Prospects and limitations for early warnings of regime shifts, Philos. Trans. R. Soc. B 370 (2015) 20130263. Crossref, Web of Science, Google Scholar
40. Dalziell, E. and McManus, S. , Resilience, vulnerability, and adaptive capacity: Implications for system performance, in 1st Int. Forum for Engineering Decision Making (2004). Google Scholar
41. De Haan, L. and Ferreira, A. , Extreme Value Theory: An Introduction (Springer Science & Business Media, 2007). Google Scholar
42. Deffuant, G. and Gilbert, N. (eds.), Viability and Resilience of Complex Systems, Understanding Complex Systems (Springer, Berlin, 2011). Crossref, Google Scholar
43. Dinh, L. T., Pasman, H., Gao, X. and Mannan, M. S. , Resilience engineering of industrial processes: Principles and contributing factors, J. Loss Prevent. Process Indust. 25 (2012) 233–241. Crossref, Web of Science, Google Scholar
44. Diveev, A. and Shmalko, E. , Symbolic regression methods, in Machine Learning Control by Symbolic Regression (Springer, 2021). Crossref, Google Scholar
45. Egeland, B., Carlson, E. and Sroufe, L. A. , Resilience as process, Develop. Psychopathol. 5 (1993) 517–528. Crossref, Web of Science, Google Scholar
46. Eisenberg, J. and Partridge, C. , The internet under crisis conditions: Learning from September 11, in Telecommunications Policy Research Conference (2003). Google Scholar
47. Elster, J. , Explaining Social Behavior: More Nuts and Bolts for the Social Sciences (Cambridge University Press, 2007). Crossref, Google Scholar
48. Flache, A., Mäs, M., Feliciani, T., Chattoe-Brown, E., Deffuant, G., Huet, S. and Lorenz, J. , Models of social influence: Towards the next frontiers, J. Artifi. Soc. Soc. Simul. 20 (2017). Web of Science, Google Scholar
49. Flache, A., Mäs, M. and Keijzer, M. A. , Computational approaches in rigorous sociology: Agent-based computational modeling and computational social science, in Handbook of Sociological Science (Edward Elgar Publishing, 2022), pp. 57–72. Crossref, Google Scholar
50. Flamino, J., Szymanski, B. K., Bahulkar, A., Chan, K. and Lizardo, O. , Creation, evolution, and dissolution of social groups. Sci. Rept. 11 (2021) 17470. Crossref, Web of Science, Google Scholar
51. Folke, C. , Resilience: The emergence of a perspective for social-ecological systems analyses, Global Environ. Change 16 (2006) 253–267. Crossref, Web of Science, Google Scholar
52. Folke, C., Carpenter, S., Elmqvist, T., Gunderson, L., Holling, C. S. and Walker, B. , Resilience and sustainable development: Building adaptive capacity in a world of transformations, J. Human Environ. 31 (2002) 437–440. Crossref, Google Scholar
53. Fraccascia, L., Giannoccaro, I. and Albino, V. , Resilience of complex systems: State of the art and directions for future research, Complexity 2018 (2018) 1–44. Crossref, Web of Science, Google Scholar
54. Francis, R. and Bekera, B. , A metric and frameworks for resilience analysis of engineered and infrastructure systems, Reliab. Eng. Syst. Saf. 121 (2014) 90–103. Crossref, Web of Science, Google Scholar
55. Freeman, S., Hirschhorn, L. and Maltz, M. , Organization resilience and moral purpose: Sandler O’Neill and partners in the aftermath of 9/11/01, in National Academy of Management Meetings, New Orleans, LA, 2004, pp. 17–26. Google Scholar
56. Gallopín, G. C. , Linkages between vulnerability, resilience, and adaptive capacity, Global Environ. Change 16 (2006) 293–303. Crossref, Web of Science, Google Scholar
57. Garas, A. (ed.), Interconnected Networks, 1st edn. (Springer International Publishing, 2016), 229 pp. Crossref, Google Scholar
58. Garas, A., Schweitzer, F. and Havlin, S. , A k-shell decomposition method for weighted networks, New J. Phys. 14 (2012) 083030. Crossref, Web of Science, Google Scholar
59. Garcia, D., Kappas, A., Küster, D. and Schweitzer, F. , The dynamics of emotions in online interaction, Roy. Soc. Open Sci. 3 (2016) 160059. Crossref, Web of Science, Google Scholar
60. Garcia, D., Mavrodiev, P. and Schweitzer, F. , Social resilience in online communities: The autopsy of Friendster, in 1st ACM Conf. on Online Social Networks (ACM Press, 2013a), pp. 39–50. Crossref, Google Scholar
61. Garcia, D., Zanetti, M. S. and Schweitzer, F. , The role of emotions in contributors activity: A case study on the Gentoo community, in Int. Conf. on Cloud and Green Computing (IEEE, 2013b), pp. 410–417. Crossref, Google Scholar
62. Goggins, S. P. and Valetto, G. , Assessing the structural fluidity of virtual organizations and its effects, in Socioinformatics—The Social Impact of Interactions between Humans and IT (Springer, 2014), pp. 121–137. Crossref, Google Scholar
63. González, A. D., Chapman, A., Dueñas-Osorio, L., Mesbahi, M. and D’Souza, R. M. , Efficient infrastructure restoration strategies using the recovery operator, Computer-Aided Civil Infrastruct. Eng. 32 (2017) 991–1006. Crossref, Web of Science, Google Scholar
64. Górski, P. J., Bochenina, K., Hołyst, J. A. and D’Souza, R. M. , Homophily based on few attributes can impede structural balance, Phys. Rev. Lett. 125 (2020) 078302. Crossref, Web of Science, Google Scholar
65. Gote, C., Casiraghi, G., Schweitzer, F. and Scholtes, I., Predicting sequences of traversed nodes in graphs using network models with multiple higher orders, arXiv:2007.06662. Google Scholar
66. Gote, C., Scholtes, I. and Schweitzer, F. , git2net: Mining time-stamped co-editing networks from large git repositories, in 16th Int. Conf. Mining Software Repositories (IEEE Press, 2019), pp. 433–444. Crossref, Google Scholar
67. Gote, C., Scholtes, I. and Schweitzer, F. , Analysing time-stamped co-editing networks in software development teams using git2net, Empir. Softw. Eng. 26 (2021) 1–41. Crossref, Web of Science, Google Scholar
68. Gote, C. and Zingg, C. , gambit – An open source name disambiguation tool for version control systems, in IEEE/ACM 18th Int. Conf. Mining Software Repositories (IEEE, 2021), pp. 80–84. Google Scholar
69. Grimm, V. and Calabrese, J. M. , What is resilience? A short introduction, in Viability and Resilience of Complex Systems, Deffuant, G. and Gilbert, N. (eds.) (Springer, 2011), pp. 3–13. Crossref, Google Scholar
70. Grodzinski, W., Cowling, E. B., Breymeyer, A. I. and Phillips, A. S. , Ecological risks: Perspectives from Poland and the United States (National Academy Press, 1990). Google Scholar
71. Guimera, R., Uzzi, B., Spiro, J. and Amaral, L. A. N. , Team assembly mechanisms determine collaboration network structure and team performance, Science 308 (2005) 697–702. Crossref, Web of Science, Google Scholar
72. Gunderson, L. H. , Ecological resilience–In theory and application, Annu. Rev. Ecol. System. 31 (2000) 425–439. Crossref, Google Scholar
73. Harary, F. , On the measurement of structural balance, Behav. Sci. 4 (1959) 316–323. Crossref, Google Scholar
74. Harrigan, N. and Yap, J. , Avoidance in negative ties: Inhibiting closure, reciprocity, and homophily, Soc. Netw. 48 (2017) 126–141. Crossref, Web of Science, Google Scholar
75. Hedström, P. and Bearman, P. , What is analytical sociology all about? An introductory essay, in Oxford Handbook of Analytical Sociology (Oxford University Press, 2009), pp. 3–24. Google Scholar
76. Helbing, D. and Balietti, S. , From social data mining to forecasting socio-economic crises, Eur. Phys. J. Spec. Top. 195 (2011) 3–68. Crossref, Web of Science, Google Scholar
77. Helfgott, A. , Operationalising systemic resilience, Eur. J. Oper. Res. 268 (2018) 852–864. Crossref, Web of Science, Google Scholar
78. Henderson, K., Gallagher, B., Eliassi-Rad, T., Tong, H., Basu, S., Akoglu, L., Koutra, D., Faloutsos, C. and Li, L. , RolX: Structural role extraction & mining in large graphs, in Proc. 18th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining (2012), pp. 1231–1239. Crossref, Google Scholar
79. Henry, D. and Ramirez-Marquez, J. E. , Generic metrics and quantitative approaches for system resilience as a function of time, Reliab. Eng. Syst. Saf. 99 (2012) 114–122. Crossref, Web of Science, Google Scholar
80. Hoegl, M. and Gemuenden, H. G. , Teamwork quality and the success of innovative projects: A theoretical concept and empirical evidence, Organ. Sci. 12 (2001) 435–449. Crossref, Web of Science, Google Scholar
81. Holling, C. S. , Resilience and stability of ecological systems, Annu. Rev. Ecol. System. 4 (1973) 1–23. Crossref, Google Scholar
82. Holling, C. S. and Gunderson, L. H. , Resilience and adaptive cycles, in Panarchy: Understanding Transformations in Human and Natural Systems (Island Press, Washington, DC, 2002), pp. 25–62. Google Scholar
83. Hollnagel, E., Woods, D. D. and Leveson, N. , Resilience Engineering: Concepts and Precepts (Ashgate Publishing, Ltd., 2007). Google Scholar
84. Hołyst, J. A., Kacperski, K. and Schweitzer, F. , Phase transitions in social impact models of opinion formation, Physica A 285 (2000) 199–210. Crossref, Web of Science, Google Scholar
85. Homans, G. C. , The Human Group (Transaction Publishers, 1950). Google Scholar
86. Hosseini, S., Barker, K. and Ramirez-Marquez, J. E. , A review of definitions and measures of system resilience, Reliab. Eng. Syst. Saf. 145 (2016) 47–61. Crossref, Web of Science, Google Scholar
87. Ifejika Speranza, C., Wiesmann, U. and Rist, S. , An indicator framework for assessing livelihood resilience in the context of social–ecological dynamics, Global Environ. Change 28 (2014) 109–119. Crossref, Web of Science, Google Scholar
88. Ilbeigi, M. , Statistical process control for analyzing resilience of transportation networks, Int. J. Disas. Risk Reduct. 33 (2019) 155–161. Crossref, Web of Science, Google Scholar
89. Jones, D. , Social evolution: The ritual animal, Nature 493 (2013) 470–472. Crossref, Web of Science, Google Scholar
90. Keck, M. and Sakdapolrak, P. , What is social resilience? Lessons learned and ways forward, Erdkunde 67 (2013) 5–19. Crossref, Web of Science, Google Scholar
91. Kerr, S. E. , Social capital as a determinant of resilience, in Resilience, Zommers, Z. and Alverson, K. (eds.) (Elsevier, 2018), pp. 267–275. Crossref, Google Scholar
92. Khodaei, A. , Resiliency-oriented microgrid optimal scheduling, IEEE Trans. Smart Grid 5 (2014) 1584–1591. Crossref, Web of Science, Google Scholar
93. Kitano, H. , Biological robustness, Nat. Rev. Genet. 5 (2004) 826–837. Crossref, Web of Science, Google Scholar
94. Kitano, M. K. and Lewis, R. B. , Resilience and coping: Implications for gifted children and youth at risk, Roeper Rev. 27 (2005) 200–205. Crossref, Google Scholar
95. Koskinen, J. and Daraganova, G. , Exponential random graph model fundamentals, in Exponential Random Graph Models for Social Networks, Lusher, D., Koskinen, J. and Robins, G. (eds.) (Cambridge University Press, 2012), pp. 49–76. Crossref, Google Scholar
96. Labianca, G. and Brass, D. J. , Exploring the social ledger: Negative relationships and negative asymmetry in social networks in organizations, Acad. Manag. Rev. 31 (2006) 596–614. Crossref, Web of Science, Google Scholar
97. Lambiotte, R., Rosvall, M. and Scholtes, I. , From networks to optimal higher-order models of complex systems, Nat. Phys. 15 (2019) 313–320. Crossref, Web of Science, Google Scholar
98. Lampel, J., Bhalla, A. and Jha, P. P. , Does governance confer organisational resilience? Evidence from UK employee owned businesses, Eur. Manag. J. 32 (2014) 66–72. Crossref, Web of Science, Google Scholar
99. Latané, B. , The psychology of social impact, Amer. Psychol. 36 (1981) 343. Crossref, Web of Science, Google Scholar
100. Lazega, E., Snijders, T. A. and Wittek, R. P. , A Research Agenda for Social Networks and Social Resilience (Edward Elgar Publishing, 2022). Google Scholar
101. Leifeld, P. and Cranmer, S. J. , A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model, Netw. Sci. 7 (2019) 20–51. Crossref, Web of Science, Google Scholar
102. Leifeld, P. and Cranmer, S. J. , The stochastic actor-oriented model is a theory as much as it is a method and must be subject to theory tests, Netw. Sci. 10 (2022) 15–19. Crossref, Web of Science, Google Scholar
103. Lengnick-Hall, C. A. and Beck, T. E. , Adaptive fit versus robust transformation: How organizations respond to environmental change, J. Manag. 31 (2005) 738–757. Google Scholar
104. Lenton, T. M., Livina, V. N., Dakos, V., van Nes, E. H. and Scheffer, M. , Early warning of climate tipping points from critical slowing down: Comparing methods to improve robustness, Philos. Trans. R. Soc. A 370 (2012) 1185–1204. Crossref, Web of Science, Google Scholar
105. Levine, S., Assessing resilience: Why quantification misses the point, Overseas Development Institute, London (2014). Google Scholar
106. Liu, Y.-Y., Slotine, J.-J. and Barabasi, A.-L. , Controllability of complex networks, Nature 473 (2011) 167–173. Crossref, Web of Science, Google Scholar
107. Lorenz, J., Battiston, S. and Schweitzer, F. , Systemic risk in a unifying framework for cascading processes on networks, Eur. Phys. J. B 71 (2009) 441–460. Crossref, Web of Science, Google Scholar
108. Luthar, S. S. , Resilience and Vulnerability: Adaptation in the Context of Childhood Adversities (Cambridge University Press, 2003). Crossref, Google Scholar
109. Maguire, B. and Hagan, P. , Disasters and communities: Understanding social resilience, Austral. J. Emerg. Manag. 22 (2007) 16–20. Google Scholar
110. Mamouni Limnios, E. A., Mazzarol, T., Ghadouani, A. and Schilizzi, S. G. , The resilience architecture framework: Four organizational archetypes, Eur. Manag. J. 32 (2014) 104–116. Crossref, Web of Science, Google Scholar
111. Marshall, N. , Understanding social resilience to climate variability in primary enterprises and industries, Global Environ. Change 20 (2010) 36–43. Crossref, Web of Science, Google Scholar
112. Masuda, N., Klemm, K. and Eguíluz, V. M. , Temporal networks: Slowing down diffusion by long lasting interactions, Phys. Rev. Lett. 111 (2013) 188701. Crossref, Web of Science, Google Scholar
113. Mavrodiev, P., Fleischmann, D., Kerth, G. and Schweitzer, F. , Quantifying individual influence in leading-following behavior of Bechstein’s bats, Sci. Rep. 11 (2021) 2691. Crossref, Web of Science, Google Scholar
114. McManus, S., Seville, E., Brunsdon, D. and Vargo, J., Resilience management: A framework for assessing and improving the resilience of organisations. Resilient Organizations Research Reports (2007). Google Scholar
115. Medeiros, L. P., Allesina, S., Dakos, V., Sugihara, G. and Saavedra, S. , Ranking species based on sensitivity to perturbations under non-equilibrium community dynamics, Ecol. Lett. 26 (2022) 170–183. Crossref, Web of Science, Google Scholar
116. Meerow, S., Newell, J. P. and Stults, M. , Defining urban resilience: A review, Landscape Urban Plann. 147 (2016) 38–49. Crossref, Web of Science, Google Scholar
117. Morone, F., Del Ferraro, G. and Makse, H. A. , The k-core as a predictor of structural collapse in mutualistic ecosystems, Nat. Phys. 15 (2019) 95–102. Crossref, Web of Science, Google Scholar
118. Morone, F. and Makse, H. A. , Influence maximization in complex networks through optimal percolation, Nature 524 (2015) 65–68. Crossref, Web of Science, Google Scholar
119. Nanumyan, V., Gote, C. and Schweitzer, F. , Multilayer network approach to modeling authorship influence on citation dynamics in physics journals, Phys. Rev. E 102 (2020) 032303. Crossref, Web of Science, Google Scholar
120. Nash, W. A. , Schaum’s Outline of Theory and Problems of Strength of Materials (McGraw-Hill, 1998). Google Scholar
121. Norris, F. H., Stevens, S. P., Pfefferbaum, B., Wyche, K. F. and Pfefferbaum, R. L. , Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness, Amer. J. Commun. Psychol. 41 (2008) 127–150. Crossref, Web of Science, Google Scholar
122. Nowak, A., Szamrej, J. and Latané, B. , From private attitude to public opinion: A dynamic theory of social impact, Psychol. Rev. 97 (1990) 362. Crossref, Web of Science, Google Scholar
123. Obrist, B., Pfeiffer, C. and Henley, R. , Multi-layered social resilience, Prog. Develop. Stud. 10 (2010) 283–293. Crossref, Web of Science, Google Scholar
124. Ostrom, E. , Understanding Institutional Diversity (Princeton University Press, 2009). Crossref, Google Scholar
125. Papanikolaou, N., Vaccario, G., Hormann, E., Lambiotte, R. and Schweitzer, F. , Consensus from group interactions: An adaptive voter model on hypergraphs, Phys. Rev. E 105 (2022) 054307. Crossref, Web of Science, Google Scholar
126. Peixoto, T. P. and Bornholdt, S. , Evolution of robust network topologies: Emergence of central backbones, Phys. Rev. Lett. 109 (2012) 118703. Crossref, Web of Science, Google Scholar
127. Petzold, J. , Social capital and small-island resilience, in Social Capital, Resilience and Adaptation on Small Islands (Springer, 2017), pp. 17–61. Crossref, Google Scholar
128. Pfitzner, R., Scholtes, I., Garas, A., Tessone, C. J. and Schweitzer, F. , Betweenness preference: Quantifying correlations in the topological dynamics of temporal networks, Phys. Rev. Lett. 110 (2013) 198701. Crossref, Web of Science, Google Scholar
129. Renschler, C., Frazier, A., Arendt, L., Cimellaro, G., Reinhorn, A. and Bruneau, M. , Developing the ‘PEOPLES’ resilience framework for defining and measuring disaster resilience at the community scale, in Proc. 9th U.S. National and 10th Canadian Conf. Earthquake Engineering (2010), pp. 1–10. Google Scholar
130. Reza, G., Alavizadeh, A. and Tarokj, M. , From system-of-systems to meta-systems: Ambiguities and challenges, in System of Systems, Gheorghe, A. V. (ed.), (InTech, 2012), pp. 1–12. Crossref, Google Scholar
131. Rivera, M. T., Soderstrom, S. B. and Uzzi, B. , Dynamics of dyads in social networks: Assortative, relational, and proximity mechanisms, Annu. Rev. Sociol. 36 (2010) 91–115. Crossref, Web of Science, Google Scholar
132. Robb, D. , Building resilient organizations, OD Practitioner 32 (2000) 27–32. Google Scholar
133. Robins, G., Pattison, P., Kalish, Y. and Lusher, D. , An introduction to exponential random graph (p*) models for social networks, Social Netw. 29 (2007) 173–191. Crossref, Web of Science, Google Scholar
134. Russo, G., Gote, C., Brandenberger, L., Schlosser, S. and Schweitzer, F., Disentangling active and passive cosponsorship in the U.S. Congress, arXiv:2205.09674. Google Scholar
135. Saavedra, S., Stouffer, D. B., Uzzi, B. and Bascompte, J. , Strong contributors to network persistence are the most vulnerable to extinction, Nature 478 (2011) 233–235. Crossref, Web of Science, Google Scholar
136. Sahebjamnia, N., Torabi, S. and Mansouri, S. , Integrated business continuity and disaster recovery planning: Towards organizational resilience, Eur. J. Oper. Res. 242 (2015) 261–273. Crossref, Web of Science, Google Scholar
137. Sanhedrai, H., Gao, J., Bashan, A., Schwartz, M., Havlin, S. and Barzel, B. , Reviving a failed network through microscopic interventions, Nat. Phys. 18 (2022) 338–349. Crossref, Web of Science, Google Scholar
138. Scheffer, M., Carpenter, S. R., Lenton, T. M., Bascompte, J., Brock, W., Dakos, V., van de Koppel, J., van de Leemput, I. A., Levin, S. A., van Nes, E. H., Pascual, M. and Vandermeer, J. , Anticipating critical transitions, Science 338 (2012) 344–348. Crossref, Web of Science, Google Scholar
139. Scholtes, I., Mavrodiev, P. and Schweitzer, F. , From Aristotle to Ringelmann: A large-scale analysis of team productivity and coordination in Open Source Software projects, Empir. Softw. Eng. 21 (2016a) 642–683. Crossref, Web of Science, Google Scholar
140. Scholtes, I., pathpy contributors, pathpy, Python package version 2.2.0 (2019). Google Scholar
141. Scholtes, I., Wider, N. and Garas, A. , Higher-order aggregate networks in the analysis of temporal networks: Path structures and centralities, Eur. Phys. J. B 89 (2016b) 1–15. Crossref, Web of Science, Google Scholar
142. Scholtes, I., Wider, N., Pfitzner, R., Garas, A., Tessone, C. J. and Schweitzer, F. , Causality-driven slow-down and speed-up of diffusion in non-Markovian temporal networks, Nat. Commun. 5 (2014) 5024. Crossref, Web of Science, Google Scholar
143. Schweighofer, S., Schweitzer, F. and Garcia, D. , A weighted balance model of opinion hyperpolarization, J. Artifi. Soc. Soc. Simul. 23 (2020) 5. Crossref, Web of Science, Google Scholar
144. Schweitzer, F. , The bigger picture: Complexity meets systems design, in Design Tales of Science and Innovation, Gerd Folkers, M. S. (ed.), (Chronos Verlag, Zurich, 2019) pp. 77–86. Google Scholar
145. Schweitzer, F. , Designing systems bottom up: Facets and problems, Adv. Compl. Syst. 23 (2020) 2020001. Link, Web of Science, Google Scholar
146. Schweitzer, F. , Social percolation revisited: From 2d lattices to adaptive network, Physica A 570 (2021) 125687. Crossref, Web of Science, Google Scholar
147. Schweitzer, F. , Agents, Networks, Evolution: A Quarter Century of Advances in Complex Systems (World Scientific, Singapore, 2022a). Link, Google Scholar
148. Schweitzer, F. , Group relations, resilience and the I Ching, Physica A 603 (2022b) 127630. Crossref, Web of Science, Google Scholar
149. Schweitzer, F. and Andres, G. , Social nucleation: Group formation as a phase transition, Phys. Rev. E 105 (2022) 044301. Crossref, Web of Science, Google Scholar
150. Schweitzer, F., Casiraghi, G., Tomasello, M. V. and Garcia, D. , Fragile, yet resilient: Adaptive decline in a collaboration network of firms, Front. Appl. Math. Statist. 7 (2021) 6. Crossref, Google Scholar
151. Schweitzer, F., Garas, A., Tomasello, M. V., Vaccario, G. and Verginer, L. , The role of network embeddedness on the selection of collaboration partners: An agent-based model with empirical validation, Adv. Compl. Syst. 25 (2022a) 2250003. Link, Web of Science, Google Scholar
152. Schweitzer, F., Mavrodiev, P., Seufert, A. M. and Garcia, D. , Modeling user reputation in online social networks: The role of costs, benefits, and reciprocity, Entropy 22 (2020a) 1073. Crossref, Web of Science, Google Scholar
153. Schweitzer, F., Zhang, Y. and Casiraghi, G. , Intervention scenarios to enhance knowledge transfer in a network of firms, Front. Phys. 8 (2020b) 382. Crossref, Web of Science, Google Scholar
154. Schweitzer, F., Zingg, C. and Casiraghi, G., Struggling with change: The fragile resilience of collectives, arXiv:2210.08224. Google Scholar
155. Seidman, S. B. , Network structure and minimum degree, Social Netw. 5 (1983) 269–287. Crossref, Web of Science, Google Scholar
156. Shai, S., Kenett, D. Y., Kenett, Y. N., Faust, M., Dobson, S. and Havlin, S., Resilience of modular complex networks, arXiv:1404.4748. Google Scholar
157. Shamsuddin, S. , Resilience resistance: The challenges and implications of urban resilience implementation, Cities 103 (2020) 102763. Crossref, Web of Science, Google Scholar
158. Sheffi, Y. and Rice, J. B. J. , A supply chain view of the resilient enterprise, MIT Sloan Manag. Rev. 47 (2005) 41–48. Web of Science, Google Scholar
159. Shenk, L., Krejci, C. and Passe, U. , Agents of change—together: Using agent-based models to inspire social capital building for resilient communities, Commun. Develop. 50 (2019) 256–272. Crossref, Web of Science, Google Scholar
160. Smit, B. and Wandel, J. , Adaptation, adaptive capacity and vulnerability, Global Environ. Change 16 (2006) 282–292. Crossref, Web of Science, Google Scholar
161. Smith, P., Hutchison, D., Sterbenz, J. P., Schöller, M., Fessi, A., Karaliopoulos, M., Lac, C. and Plattner, B. , Network resilience: A systematic approach, IEEE Commun. Mag. 49 (2011) 88–97. Crossref, Web of Science, Google Scholar
162. Snijders, T. A. , Stochastic actor-oriented models for network dynamics, Annu. Rev. Statist. Appl. 4 (2017) 343–363. Crossref, Web of Science, Google Scholar
163. Stephens, T., gplearn contributors, gplearn, Python package version 0.4.2 (2022). Google Scholar
164. Sterbenz, J. P., Hutchison, D., Çetinkaya, E. K., Jabbar, A., Rohrer, J. P., Schöller, M. and Smith, P. , Resilience and survivability in communication networks: Strategies, principles, and survey of disciplines, Comput. Netw. 54 (2010) 1245–1265. Crossref, Web of Science, Google Scholar
165. Sutcliffe, K. and Vogus, T. J. , Organizing for resilience, in Positive Organizational Scholarship: Foundations of a New Discpline (Berret-Koehler, San Francisco, 2003), pp. 94–110. Google Scholar
166. Tamvakis, P. and Xenidis, Y. , Comparative evaluation of resilience quantification methods for infrastructure systems, Procedia — Social Behav. Sci. 74 (2013) 339–348. Crossref, Google Scholar
167. Teekens, T., Giardini, F., Zuidersma, J. and Wittek, R. , Shaping resilience: How work team characteristics affect occupational commitment in health care interns during a pandemic, Eur. Soc. 23 (2021) S513–S529. Crossref, Web of Science, Google Scholar
168. Teo, M., Goonetilleke, A. and Ziyath, A. , An integrated framework for assessing community resilience in disaster management, in Proc. 9th Annual Int. Conf. International Institute for Infrastructure Renewal and Reconstruction (Queensland University of Technology, 2015), pp. 309–314. Google Scholar
169. Ureña-Carrion, J., Saramäki, J. and Kivelä, M. , Estimating tie strength in social networks using temporal communication data, EPJ Data Sci. 9 (2020) 37. Crossref, Web of Science, Google Scholar
170. Valdez, L. D., Shekhtman, L., La Rocca, C. E., Zhang, X., Buldyrev, S. V., Trunfio, P. A., Braunstein, L. A. and Havlin, S. , Cascading failures in complex networks, J. Compl. Netw. 8 (2020) cnaa013. Crossref, Web of Science, Google Scholar
171. Villavicencio-Ayub, E., Jurado-Cárdenas, S. and Valencia-Cruz, A. , Work engagement and occupational burnout: Its relation to organizational socialization and psychological resilience, J. Behav. Health Soc. Issues 6 (2015) 45–55. Crossref, Google Scholar
172. Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey, C. J., Polat, İ., Feng, Y., Moore, E. W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E. A., Harris, C. R., Archibald, A. M., Ribeiro, A. H., Pedregosa, F. and van Mulbregt, P. , SciPy 1.0 contributors, SciPy 1.0: Fundamental algorithms for scientific computing in Python, Nature Methods 17 (2020) 261–272. Crossref, Web of Science, Google Scholar
173. Vogus, T. and Sutcliffe, K. , Organizational resilience: Towards a theory and research agenda, in IEEE Int. Conf. on Systems, Man and Cybernetics (IEEE, 2007), pp. 3418–3422. Crossref, Google Scholar
174. Vugrin, E. D., Warren, D. E. and Ehlen, M. A. , A resilience assessment framework for infrastructure and economic systems: Quantitative and qualitative resilience analysis of petrochemical supply chains to a hurricane, Process Saf. Prog. 30 (2011) 280–290. Crossref, Web of Science, Google Scholar
175. Walker, B., Gunderson, L., Kinzig, A., Folke, C., Carpenter, S. and Schultz, L. , A handful of heuristics and some propositions for understanding resilience in social-ecological systems, Ecol. Soc. 11 (2006) Aritlce No. 13. Crossref, Web of Science, Google Scholar
176. Walker, B., Holling, C. S., Carpenter, S. R. and Kinzig, A. , Resilience, adaptability and transformability in social-ecological systems, Ecol. Soc. 9 (2004) Article No. 5. Crossref, Web of Science, Google Scholar
177. Walker, B. and Salt, D. , Assessing resilience, in Resilience Practice (Island Press/Center for Resource Economics, Washington, DC, 2012), pp. 67–105. Crossref, Google Scholar
178. Wang, X., Koç, Y., Kooij, R. E. and Van Mieghem, P. , A network approach for power grid robustness against cascading failures, in 7th Int. Workshop on Reliable Networks Design and Modeling (IEEE, 2015), pp. 208–214. Crossref, Google Scholar
179. Wasserman, S. and Faust, K. , Social Network Analysis (Cambridge University Press, 1994). Crossref, Google Scholar
180. Wildavsky, A. B. , Searching for Safety, Vol. 10 (Transaction Publishers, 1988). Google Scholar
181. Wuellner, D. R., Roy, S. and D’Souza, R. M. , Resilience and rewiring of the passenger airline networks in the United States, Phys. Rev. E 82 (2010) 056101. Crossref, Web of Science, Google Scholar
182. Xuan, Q., Fang, H., Fu, C. and Filkov, V. , Temporal motifs reveal collaboration patterns in online task-oriented networks, Phys. Rev. E 91 (2015) 052813. Crossref, Web of Science, Google Scholar
183. Zanetti, M. S., Scholtes, I., Tessone, C. J. and Schweitzer, F. , The rise and fall of a central contributor: Dynamics of social organization and performance in the GENTOO community, in Cooperative and Human Aspects of Software Engineering (2013), pp. 49–56. Crossref, Google Scholar
184. Zhang, Y., Garas, A. and Scholtes, I. , Higher-order models capture changes in controllability of temporal networks, J. Phys.: Compl. 2 (2020) 015007. Crossref, Google Scholar
185. Zhang, Y., Garas, A. and Schweitzer, F. , Value of peripheral nodes in controlling multilayer scale-free networks, Phys. Rev. E 93 (2016) 012309. Crossref, Web of Science, Google Scholar
186. Zhang, Y., Garas, A. and Schweitzer, F. , Control contribution identifies top driver nodes in complex networks, Adv. Compl. Syst. 22 (2019) 1950014. Link, Web of Science, Google Scholar
187. Zingg, C., Casiraghi, G., Vaccario, G. and Schweitzer, F. , What is the entropy of a social organization? Entropy 21 (2019) 901. Crossref, Web of Science, Google Scholar