- Feb 2023
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docdrop.org docdrop.org
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Kawakatsu et al. (1) make an important ad-vance in the quest for this kind of understanding, pro-viding a general model for how subtle differences inindividual-level decision-making can lead to hard-to-miss consequences for society as a whole.Their work (1) reveals two distinct regimes—oneegalitarian, one hierarchical—that emerge fromshifts in individual-level judgment. These lead to sta-tistical methods that researchers can use to reverseengineer observed hierarchies, and understand howsignaling systems work when prestige and power arein play.
M. Kawakatsu, P. S. Chodrow, N. Eikmeier, D. B. Larremore, Emergence of hierarchy in networked endorsement dynamics. Proc. Natl. Acad. Sci. U.S.A. 118, e2015188118 (2021)
This may be of interest to Jerry Michalski et al.
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- Nov 2022
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blog.mahabali.me blog.mahabali.me
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https://blog.mahabali.me/pedagogy/pedagogical-snacking-transforming-classroom-dynamics/
Providing a snack break during classes can dramatically improve the participants' participation and cohesion.
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- Jan 2021
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Landry. N., Restrepo. J. G. (2020).The effect of heterogeneity on hypergraph contagion models. Physics and Society. Retrieved from: https://arxiv.org/abs/2006.15453
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- Sep 2020
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Miyoshi, S., Jusup, M., & Holme, P. (2020). Flexible imitation mechanisms suppress epidemics through better vaccination. ArXiv:2009.00443 [Physics, q-Bio]. http://arxiv.org/abs/2009.00443
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- Aug 2020
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Velásquez-Rojas, F., Ventura, P. C., Connaughton, C., Moreno, Y., Rodrigues, F. A., & Vazquez, F. (2020). Disease and information spreading at different speeds in multiplex networks. Physical Review E, 102(2), 022312. https://doi.org/10.1103/PhysRevE.102.022312
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Jinjarak, Y., Ahmed, R., Nair-Desai, S., Xin, W., & Aizenman, J. (2020). Accounting for Global COVID-19 Diffusion Patterns, January-April 2020 (Working Paper No. 27185; Working Paper Series). National Bureau of Economic Research. https://doi.org/10.3386/w27185
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Willem, L., Hoang, T. V., Funk, S., Coletti, P., Beutels, P., & Hens, N. (2020). SOCRATES: An online tool leveraging a social contact data sharing initiative to assess mitigation strategies for COVID-19 [Preprint]. Epidemiology. https://doi.org/10.1101/2020.03.03.20030627
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Zhang, J., Litvinova, M., Liang, Y., Wang, Y., Wang, W., Zhao, S., Wu, Q., Merler, S., Viboud, C., Vespignani, A., Ajelli, M., & Yu, H. (2020). Changes in contact patterns shape the dynamics of the COVID-19 outbreak in China. Science, eabb8001. https://doi.org/10.1126/science.abb8001
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- May 2020
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psyarxiv.com psyarxiv.com
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Golino, H., Christensen, A. P., Moulder, R. G., Kim, S., & Boker, S. M. (2020, April 14). Modeling latent topics in social media using Dynamic Exploratory Graph Analysis: The case of the right-wing and left-wing trolls in the 2016 US elections. https://doi.org/10.31234/osf.io/tfs7c
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Liu, Y., Eggo, R. M., & Kucharski, A. J. (2020). Secondary attack rate and superspreading events for SARS-CoV-2. The Lancet, 395(10227), e47. https://doi.org/10.1016/S0140-6736(20)30462-1
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science.sciencemag.org science.sciencemag.org
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Pichler, Anton, Marco Pangallo, R. Maria del Rio-Chanona, François Lafond, and J. Doyne Farmer. “Production Networks and Epidemic Spreading: How to Restart the UK Economy?” ArXiv:2005.10585 [Physics, q-Fin], May 21, 2020. http://arxiv.org/abs/2005.10585.
Tags
- unemployment
- supply
- GDP
- reopening industry
- lang:en
- consumption
- demand
- economics
- transmission rate
- is:article
- social distincing
- COVID-19
- inventory dynamics
- input-output constraints
- epidemiology
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- United Kingdom
- work from home
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www.annualreviews.org www.annualreviews.org
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Edelmann, A., Wolff, T., Montagne, D., & Bail, C. A. (2020). Computational Social Science and Sociology. Annual Review of Sociology, 46(1), annurev-soc-121919-054621. https://doi.org/10.1146/annurev-soc-121919-054621
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sfi-edu.s3.amazonaws.com sfi-edu.s3.amazonaws.com
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The Santa Fe Institute - SFI Transmission PDF
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jamanetwork.com jamanetwork.com
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Steinbrook, R. (2020). Contact Tracing, Testing, and Control of COVID-19—Learning From Taiwan. JAMA Internal Medicine. https://doi.org/10.1001/jamainternmed.2020.2072
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Inglesby, T. V. (2020). Public Health Measures and the Reproduction Number of SARS-CoV-2. JAMA. https://doi.org/10.1001/jama.2020.7878
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Liu, L., Wang, X., Tang, S., & Zheng, Z. (2020). Complex social contagion induces bistability on multiplex networks. ArXiv:2005.00664 [Physics]. http://arxiv.org/abs/2005.00664
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Martins, A. C. R. (2020). Extremism definitions in opinion dynamics models. ArXiv:2004.14548 [Nlin, Physics:Physics]. http://arxiv.org/abs/2004.14548
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psyarxiv.com psyarxiv.com
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Rotella, A. M., & Mishra, S. (2020, April 24). Personal relative deprivation negatively predicts engagement in group decision-making. https://doi.org/10.31234/osf.io/6d35w
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- Apr 2020
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Leitner, S. (2020, April 18). On the dynamics emerging from pandemics and infodemics. https://doi.org/10.31234/osf.io/nqru6
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Han, L., Lin, Z., Tang, M., Zhou, J., Zou, Y., & Guan, S. (2020). Impact of contact preference on social contagions on complex networks. Physical Review E, 101(4), 042308. https://doi.org/10.1103/PhysRevE.101.042308
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Xu, S., & Li, Y. (2020). Beware of the second wave of COVID-19. The Lancet, S014067362030845X. https://doi.org/10.1016/S0140-6736(20)30845-X
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Government of Canada. (2020). Government of Canada funds 49 additional COVID-19 research projects – Details of the funded projects. Canada.ca. https://www.canada.ca/en/institutes-health-research/news/2020/03/government-of-canada-funds-49-additional-covid-19-research-projects-details-of-the-funded-projects.html
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marlin-prod.literatumonline.com marlin-prod.literatumonline.com
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Liao, H., Zhang, L., Marley, G., Tang, W. (2020). Differentiating COVID-19 response strategies. University of North Carolina Project-China. DOI: 10.1016/j.xinn.2020.04.003
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doi.org doi.org
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Atchison, C. J., Bowman, L., Vrinten, C., Redd, R., Pristera, P., Eaton, J. W., & Ward, H. (2020). Perceptions and behavioural responses of the general public during the COVID-19 pandemic: A cross-sectional survey of UK Adults [Preprint]. Public and Global Health. https://doi.org/10.1101/2020.04.01.20050039
Tags
- prevention
- lang:en
- lockdown
- perception
- self-isolation
- UK
- modeling
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- COVID-19
- data collection
- statistics
- response
- demographics
- quarentine
- adult
- economy
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- behavior
- cross-sectional
- face mask
- policy
- risk perception
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- social distancing
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