Dose–response functions and surrogate models for exploring social contagion in the Copenhagen Networks Study
暂无分享,去创建一个
J. Heitzig | S. Lehmann | J. Donges | J. Vollmer | M. Wiedermann | Niklas H. Kitzmann | Jakob H. Lochner
[1] J. Heitzig,et al. Social tipping processes towards climate action: A conceptual framework , 2022, Ecological Economics.
[2] B. LeBaron,et al. Nonlinear Dynamics and Stock Returns , 2021, Cycles and Chaos in Economic Equilibrium.
[3] Valerio Capraro,et al. Mathematical foundations of moral preferences , 2021, Journal of the Royal Society Interface.
[4] T. Lenton,et al. Upward-scaling tipping cascades to meet climate goals: plausible grounds for hope , 2021, Climate Policy.
[5] S. Lehmann,et al. The scales of human mobility , 2020, Nature.
[6] J. Heitzig,et al. Social Tipping Processes for Sustainability: An Analytical Framework , 2020, SSRN Electronic Journal.
[7] D. Brockmann,et al. COVID-19 lockdown induces disease-mitigating structural changes in mobility networks , 2020, Proceedings of the National Academy of Sciences.
[8] M. Suzman. Analytical framework , 2020, Decarbonising Urban Mobility with Land Use and Transport Policies: The Case of Auckland, New Zealand.
[9] Luna Yue Huang,et al. The effect of large-scale anti-contagion policies on the COVID-19 pandemic , 2020, Nature.
[10] Yong-Yeol Ahn,et al. The effectiveness of backward contact tracing in networks , 2020, Nature Physics.
[11] D. Brockmann,et al. Effective containment explains subexponential growth in recent confirmed COVID-19 cases in China , 2020, Science.
[12] I. Otto,et al. Social tipping dynamics for stabilizing Earth’s climate by 2050 , 2020, Proceedings of the National Academy of Sciences.
[13] M. Kummu,et al. Feeding ten billion people is possible within four terrestrial planetary boundaries , 2020, Nature Sustainability.
[14] Arkadiusz Stopczynski,et al. Interaction data from the Copenhagen Networks Study , 2019, Scientific Data.
[15] Marc Wiedermann,et al. A network-based microfoundation of Granovetter’s threshold model for social tipping , 2019, Scientific Reports.
[16] Pawel Romanczuk,et al. Individual and collective encoding of risk in animal groups , 2019, Proceedings of the National Academy of Sciences.
[17] Matthew C. Ives,et al. Sensitive intervention points in the post-carbon transition , 2019, Science.
[18] W. Willett,et al. Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems , 2019, The Lancet.
[19] Arkadiusz Stopczynski,et al. How Physical Proximity Shapes Complex Social Networks , 2018, Scientific Reports.
[20] J Runge,et al. Causal network reconstruction from time series: From theoretical assumptions to practical estimation. , 2018, Chaos.
[21] Taro Takaguchi,et al. Randomized reference models for temporal networks , 2018, SIAM Rev..
[22] Niki Frantzeskaki,et al. Positive tipping points in a rapidly warming world , 2018 .
[23] Arkadiusz Stopczynski,et al. Optimizing targeted vaccination across cyber–physical networks: an empirically based mathematical simulation study , 2017, Journal of The Royal Society Interface.
[24] S. Sorrell,et al. Sociotechnical transitions for deep decarbonization , 2017, Science.
[25] Elizabeth L. Ogburn. Challenges to Estimating Contagion Effects from Observational Data , 2017, 1706.08440.
[26] Piotr Sapiezynski,et al. Academic performance and behavioral patterns , 2017, EPJ Data Science.
[27] Piotr Sapiezynski,et al. The role of gender in social network organization , 2017, PloS one.
[28] Sune Lehmann,et al. Class attendance, peer similarity, and academic performance in a large field study , 2017, PloS one.
[29] K. Arrow,et al. Social norms as solutions , 2016, Science.
[30] Piotr Sapiezynski,et al. Evidence for a conserved quantity in human mobility , 2016, Nature Human Behaviour.
[31] Sune Lehmann,et al. Measure of Node Similarity in Multilayer Networks , 2016, PloS one.
[32] Jürgen Kurths,et al. Identifying causal gateways and mediators in complex spatio-temporal systems , 2015, Nature Communications.
[33] Jürgen Kurths,et al. Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes , 2015, Physical review. E.
[34] C. Spearman. The proof and measurement of association between two things. , 2015, International journal of epidemiology.
[35] H. Peyton Young,et al. The Evolution of Social Norms , 2015 .
[36] Arkadiusz Stopczynski,et al. Fundamental structures of dynamic social networks , 2015, Proceedings of the National Academy of Sciences.
[37] Wolfgang Lucht,et al. Macroscopic description of complex adaptive networks coevolving with dynamic node states. , 2015, Physical review. E, Statistical, nonlinear, and soft matter physics.
[38] Ciro Cattuto,et al. Compensating for population sampling in simulations of epidemic spread on temporal contact networks , 2015, Nature Communications.
[39] Jakob Eg Larsen,et al. Inferring human mobility from sparse low accuracy mobile sensing data , 2014, UbiComp Adjunct.
[40] Jeffrey T. Hancock,et al. Experimental evidence of massive-scale emotional contagion through social networks , 2014, Proceedings of the National Academy of Sciences.
[41] Jobst Heitzig,et al. How dead ends undermine power grid stability , 2014, Nature Communications.
[42] Michael W. Macy,et al. The Social Contagion of Generosity , 2014, PloS one.
[43] Piotr Sapiezynski,et al. Measuring Large-Scale Social Networks with High Resolution , 2014, PloS one.
[44] Sune Lehmann,et al. The Strength of Friendship Ties in Proximity Sensor Data , 2014, PloS one.
[45] Nicholas A. Christakis,et al. Breaking Up Is Hard to Do, Unless Everyone Else Is Doing It Too: Social Network Effects on Divorce in a Longitudinal Sample , 2013, Social forces; a scientific medium of social study and interpretation.
[46] Thomas E. Currie,et al. War, space, and the evolution of Old World complex societies , 2013, Proceedings of the National Academy of Sciences.
[47] Kristina Lerman,et al. The Simple Rules of Social Contagion , 2013, Scientific Reports.
[48] Cameron Marlow,et al. A 61-million-person experiment in social influence and political mobilization , 2012, Nature.
[49] Petter Holme,et al. Threshold model of cascades in temporal networks , 2012, ArXiv.
[50] R. Pastor-Satorras,et al. Activity driven modeling of time varying networks , 2012, Scientific Reports.
[51] Jari Saramäki,et al. Temporal Networks , 2011, Encyclopedia of Social Network Analysis and Mining.
[52] N. Christakis,et al. Social network determinants of depression , 2011, Molecular Psychiatry.
[53] N. Christakis,et al. Social network determinants of depression , 2010, Molecular Psychiatry.
[54] Ed H. Chi,et al. Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network , 2010, 2010 IEEE Second International Conference on Social Computing.
[55] Gordon Pipa,et al. Transfer entropy—a model-free measure of effective connectivity for the neurosciences , 2010, Journal of Computational Neuroscience.
[56] J. Murabito,et al. The Spread of Alcohol Consumption Behavior in a Large Social Network , 2010, Annals of Internal Medicine.
[57] N. Christakis,et al. Alone in the Crowd: The Structure and Spread of Loneliness in a Large Social Network , 2009 .
[58] Harry Eugene Stanley,et al. Catastrophic cascade of failures in interdependent networks , 2009, Nature.
[59] N. Christakis,et al. Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study , 2008, BMJ : British Medical Journal.
[60] Marco Gonzalez,et al. Author's Personal Copy Social Networks Tastes, Ties, and Time: a New Social Network Dataset Using Facebook.com , 2022 .
[61] N. Christakis,et al. SUPPLEMENTARY ONLINE MATERIAL FOR: The Collective Dynamics of Smoking in a Large Social Network , 2022 .
[62] Thilo Gross,et al. Adaptive coevolutionary networks: a review , 2007, Journal of The Royal Society Interface.
[63] N. Christakis,et al. The Spread of Obesity in a Large Social Network Over 32 Years , 2007, The New England journal of medicine.
[64] J. Kurths,et al. Reciprocity of networks with degree correlations and arbitrary degree sequences. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.
[65] C. Simmer,et al. Statistical characteristics of surrogate data based on geophysical measurements , 2006 .
[66] M. Newman,et al. Nonequilibrium phase transition in the coevolution of networks and opinions. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[67] Thilo Gross,et al. Epidemic dynamics on an adaptive network. , 2005, Physical review letters.
[68] L. Stone,et al. Generating uniformly distributed random networks. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.
[69] M. Whitlock. Combining probability from independent tests: the weighted Z‐method is superior to Fisher's approach , 2005, Journal of evolutionary biology.
[70] Michael Small,et al. The method of surrogate data , 2005 .
[71] D. Watts,et al. A generalized model of social and biological contagion. , 2005, Journal of theoretical biology.
[72] A. Arenas,et al. Models of social networks based on social distance attachment. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.
[73] Peter Sheridan Dodds,et al. Universal behavior in a generalized model of contagion. , 2004, Physical review letters.
[74] Alessandro Vespignani,et al. Incomplete ordering of the voter model on small-world networks , 2002, cond-mat/0210465.
[75] K. Sneppen,et al. Detection of topological patterns in complex networks: correlation profile of the internet , 2002, cond-mat/0205379.
[76] K. Sneppen,et al. Specificity and Stability in Topology of Protein Networks , 2002, Science.
[77] Duncan J Watts,et al. A simple model of global cascades on random networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[78] T. Schreiber,et al. Surrogate time series , 1999, chao-dyn/9909037.
[79] R. Montgomery. The Diffusion of Religions: A Sociological Perspective , 1996 .
[80] R. Stark. Why religious movements succeed or fail: A revised general model , 1996 .
[81] J. Theiler,et al. Constrained-realization Monte-Carlo method for hypothesis testing , 1996, comp-gas/9603001.
[82] W. Pritchard,et al. Dimensional analysis of resting human EEG. II: Surrogate-data testing indicates nonlinearity but not low-dimensional chaos. , 1995, Psychophysiology.
[83] T. Valente,et al. Network models of the diffusion of innovations , 1995, Comput. Math. Organ. Theory.
[84] B. Marcus,et al. The transtheoretical model: applications to exercise behavior. , 1994, Medicine and science in sports and exercise.
[85] S. Lohmann. The Dynamics of Informational Cascades: The Monday Demonstrations in Leipzig, East Germany, 1989–91 , 1994, World Politics.
[86] James Theiler,et al. Testing for nonlinearity in time series: the method of surrogate data , 1992 .
[87] I. Ajzen. The theory of planned behavior , 1991 .
[88] W. Kannel,et al. The Framingham Offspring Study. Design and preliminary data. , 1975, Preventive medicine.
[89] R. Holley,et al. Ergodic Theorems for Weakly Interacting Infinite Systems and the Voter Model , 1975 .
[90] J. Coleman,et al. Medical Innovation: A Diffusion Study. , 1967 .
[91] E. Suchman,et al. The American Soldier: Adjustment During Army Life. , 1949 .
[92] Yong-Yeol Ahn. Complex Spreading Phenomena in Social Systems , 2018 .
[93] Bernd Blasius,et al. Adaptive Networks , 2009 .
[94] Ivar Kolstad. The evolution of social norms , 2003 .
[95] H. Byrne,et al. Mathematical Biology , 2002 .
[96] A. Bandura. Social cognitive theory of personality. , 1999 .
[97] J. Prochaska,et al. The transtheoretical model: Applications to exercise. , 1994 .
[98] J. Zuzanek,et al. Leisure Behaviour and Experiences as Part of Everyday Life: The Weekly Rhythm , 1993 .
[99] M. Casdagli. Chaos and Deterministic Versus Stochastic Non‐Linear Modelling , 1992 .
[100] P. Allhoff,et al. The Framingham Offspring Study , 1991 .
[101] C. Spearman. The proof and measurement of association between two things. By C. Spearman, 1904. , 1987, The American journal of psychology.
[102] Robert C. Wolpert,et al. A Review of the , 1985 .
[103] S. Stouffer. Adjustment during army life , 1977 .
[104] N. Rashevsky,et al. Mathematical biology , 1961, Connecticut medicine.
[105] E. Suchman,et al. The American soldier: Adjustment during army life. (Studies in social psychology in World War II), Vol. 1 , 1949 .