The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Saving Human Lives: What Complexity Science and Information Systems can Contribute
Open accessAbstract
We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.
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Cites
Early-warning signals for critical transitions
Scheffer, M., Bascompte, J., Brock, W. A., Brovkin, V., Carpenter, S. R., Dakos, V., Held, H., van Nes, E. H., Rietkerk, M., & Sugihara, G. (2009) · Nature · doi:10.1038/nature08227 · Cited by 4,854
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
Globally networked risks and how to respond
Helbing, D. (2013) · Nature · doi:10.1038/nature12047 · Cited by 1,281
Self-citationThe Hidden Geometry of Complex, Network-Driven Contagion Phenomena
Brockmann, D., & Helbing, D. (2013) · Science · doi:10.1126/science.1245200 · Cited by 1,253
Self-citationHow simple rules determine pedestrian behavior and crowd disasters
Moussaïd, M., Helbing, D., & Theraulaz, G. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1016507108 · Cited by 1,204
Self-citationThe Price of Prisons: What Incarceration Costs Taxpayers
Henrichson, C., & Delaney, R. (2012) · Federal Sentencing Reporter · doi:10.1525/fsr.2012.25.1.68 · Cited by 181
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Economic and social consequences of human mobility restrictions under COVID-19
Bonaccorsi, G., Pierri, F., Cinelli, M., Flori, A., Galeazzi, A., Porcelli, F., Schmidt, A. L., Valensise, C. M., Scala, A., Quattrociocchi, W., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2007658117 · Cited by 1,004
Behavioural change models for infectious disease transmission: a systematic review (2010–2015)
Verelst, F., Willem, L., & Beutels, P. (2016) · Journal of The Royal Society Interface · doi:10.1098/rsif.2016.0820 · Cited by 382
Automatic cyberbullying detection: A systematic review
Rosa, H., Pereira, N., Ribeiro, R., Ferreira, P. C., Carvalho, J. P., Oliveira, S., Coheur, L., Paulino, P., Veiga Simão, A. M., & Trancoso, I. (2019) · Computers in Human Behavior · doi:10.1016/j.chb.2018.12.021 · Cited by 307
Rate and Energy Efficiency Improvements for 5G-Based IoT with Simultaneous Transfer
Liu, X., & Zhang, X. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2863267 · Cited by 176
Predicting armed conflict: Time to adjust our expectations?
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Metadata
- Authors
- Helbing, D., Brockmann, D., Chadefaux, T., Donnay, K., Blanke, U., Woolley-Meza, O., Moussaid, M., Johansson, A., Krause, J., Schutte, S., & Perc, M.
- Venue
- Journal of Statistical Physics
- Published
- 2014-06-05
- Volume
- 158
- Issue
- 3
- Pages
- 735-781
- ISSN
- 0022-4715 (ISSN-L)
- 1572-9613
- OpenAlex
- W2138890315
- Cited by
- 615
- References
- 6
- FWCI
- 14.72
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Helbing, D., Brockmann, D., Chadefaux, T., Donnay, K., Blanke, U., Woolley-Meza, O., Moussaid, M., Johansson, A., Krause, J., Schutte, S., & Perc, M. (2015). Saving Human Lives: What Complexity Science and Information Systems can Contribute. Journal of Statistical Physics. https://doi.org/10.1007/s10955-014-1024-9
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
