- Nov 2022
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twitter.com twitter.comTwitter1
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v5: added git and github (thanks @ceejbot), and RSS (thanks @zem42). Taking suggestions for hierarchical/distributed and hierarchical/decentralized.
t Laurie Voss's crowdsourced set of examples of things that have structure & control in the form of the following: - centralized - hierarchical - federated - distributed - decentralized
Picture below: Link to tweet: https://twitter.com/seldo/status/1486563446099300359?s=20&t=C6z9xUF_YBkOFmfcjfjpUA
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- Dec 2021
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arxiv.org arxiv.org
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Kan, U., Feng, M., & Porter, M. A. (2021). An Adaptive Bounded-Confidence Model of Opinion Dynamics on Networks. ArXiv:2112.05856 [Physics]. http://arxiv.org/abs/2112.05856
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- Jul 2021
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link.aps.org link.aps.org
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Wang, B., Gou, M., Guo, Y., Tanaka, G., & Han, Y. (2020). Network structure-based interventions on spatial spread of epidemics in metapopulation networks. Physical Review E, 102(6), 062306. https://doi.org/10.1103/PhysRevE.102.062306
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- Jun 2021
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arxiv.org arxiv.org
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Persoon, P. G. J. (2021). Cumulative structure and path length in networks of knowledge. ArXiv:2106.10480 [Physics]. http://arxiv.org/abs/2106.10480
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- Mar 2021
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Karimi, Fariba, and Petter Holme. ‘A Temporal Network Version of Watts’s Cascade Model’. ArXiv:2103.13604 [Physics], 25 March 2021. http://arxiv.org/abs/2103.13604.
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arxiv.org arxiv.org
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Barrat, A., de Arruda, G. F., Iacopini, I., & Moreno, Y. (2021). Social contagion on higher-order structures. ArXiv:2103.03709 [Physics]. http://arxiv.org/abs/2103.03709
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- Sep 2020
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iriss.stanford.edu iriss.stanford.edu
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2020 Conference on Computational Sociology | IRiSS. (n.d.). Retrieved 30 September 2020, from https://iriss.stanford.edu/css/conferences/2020-conference-computational-sociology
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Chen, Q., & Porter, M. A. (2020). Epidemic Thresholds of Infectious Diseases on Tie-Decay Networks. ArXiv:2009.12932 [Physics]. http://arxiv.org/abs/2009.12932
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Peel, L., & Schaub, M. T. (2020). Detectability of hierarchical communities in networks. ArXiv:2009.07525 [Physics, Stat]. http://arxiv.org/abs/2009.07525
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- Aug 2020
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Young, J.-G., Cantwell, G. T., & Newman, M. E. J. (2020). Robust Bayesian inference of network structure from unreliable data. ArXiv:2008.03334 [Physics, Stat]. http://arxiv.org/abs/2008.03334
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www.nber.org www.nber.org
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Kuchler, T., Russel, D., & Stroebel, J. (2020). The Geographic Spread of COVID-19 Correlates with Structure of Social Networks as Measured by Facebook (Working Paper No. 26990; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w26990
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Alfaro, L., Faia, E., Lamersdorf, N., & Saidi, F. (2020). Social Interactions in Pandemics: Fear, Altruism, and Reciprocity (Working Paper No. 27134; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27134
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- Jul 2020
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Laliotis, I., & Minos, D. (2020). Spreading the disease: The role of culture [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/z4ndc
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- Jun 2020
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Zhang, L., & Peixoto, T. P. (2020). Statistical inference of assortative community structures. ArXiv:2006.14493 [Cond-Mat, Physics:Physics, Stat]. http://arxiv.org/abs/2006.14493
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Murphy, C., Laurence, E., & Allard, A. (2020). Deep learning of stochastic contagion dynamics on complex networks. ArXiv:2006.05410 [Cond-Mat, Physics:Physics, Stat]. http://arxiv.org/abs/2006.05410
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Tann, W. J.-W., Chang, E.-C., & Hooi, B. (2020). SHADOWCAST: Controlling Network Properties to Explain Graph Generation. ArXiv:2006.03774 [Cs, Stat]. http://arxiv.org/abs/2006.03774
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iaciac.github.io iaciac.github.io
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Iacopini, I. (2020, June 3). Networks beyond pairwise interactions: Structure and dynamics. Iacopo Iacopini. https://iaciac.github.io/post/beyond/
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Gurfinkel, A. J., & Rikvold, P. A. (2020). A Current-Flow Centrality With Adjustable Reach. ArXiv:2005.14356 [Physics]. http://arxiv.org/abs/2005.14356
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Mariani, M. S., & Lü, L. (2020). Network-based ranking in social systems: Three challenges. Journal of Physics: Complexity, 1(1), 011001. https://doi.org/10.1088/2632-072X/ab8a61
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Eroglu, D. (2020). Revealing Dynamics, Communities, and Criticality from Data. Physical Review X, 10(2). https://doi.org/10.1103/PhysRevX.10.021047
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- May 2020
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arxiv.org arxiv.org
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O’Keeffe, K. P., Griffith, V., Xu, Y., Santi, P., & Ratti, C. (2020). The darkweb: A social network anomaly. ArXiv:2005.14023 [Nlin, Physics:Physics]. http://arxiv.org/abs/2005.14023
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Peixoto, T. P. (2020). Revealing consensus and dissensus between network partitions. ArXiv:2005.13977 [Physics, Stat]. http://arxiv.org/abs/2005.13977
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Rosenblatt, S. F., Smith, J. A., Gauthier, G. R., & Hébert-Dufresne, L. (2020). Immunization Strategies in Networks with Missing Data. ArXiv:2005.07632 [Physics, q-Bio]. http://arxiv.org/abs/2005.07632
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link.aps.org link.aps.org
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Vasques Filho, D., & O’Neale, D. R. J. (2020). Transitivity and degree assortativity explained: The bipartite structure of social networks. Physical Review E, 101(5), 052305. https://doi.org/10.1103/PhysRevE.101.052305
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Riolo, M. A., & Newman, M. E. J. (2020). Consistency of community structure in complex networks. Physical Review E, 101(5), 052306. https://doi.org/10.1103/PhysRevE.101.052306
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www.nature.com www.nature.com
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Li, A., Zhou, L., Su, Q., Cornelius, S. P., Liu, Y.-Y., Wang, L., & Levin, S. A. (2020). Evolution of cooperation on temporal networks. Nature Communications, 11(1), 1–9. https://doi.org/10.1038/s41467-020-16088-w
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