Dose–response functions and surrogate models for exploring social contagion in the Copenhagen Networks Study

[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 .