Entropy as a Measure of Attractiveness and Socioeconomic Complexity in Rio de Janeiro Metropolitan Area
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Alexandre G. Evsukoff | Horacio Samaniego | Maxime Lenormand | Moacyr A. H. B. da Silva | Julio C. Chaves | Vinicius F. Vieira | Maxime Lenormand | H. Samaniego | M. A. Silva | Julio C. Chaves | Alexandre Evsukoff | V. F. Vieira
[1] Teodoro Dannemann,et al. The time geography of segregation during working hours , 2018, Royal Society Open Science.
[2] Michael Batty,et al. Big data, smart cities and city planning , 2013, Dialogues in human geography.
[3] Huiping Li,et al. Residential Segregation, Spatial Mismatch and Economic Growth across US Metropolitan Areas , 2013 .
[4] Zbigniew Smoreda,et al. An analytical framework to nowcast well-being using mobile phone data , 2016, International Journal of Data Science and Analytics.
[5] Albert-László Barabási,et al. Understanding individual human mobility patterns , 2008, Nature.
[6] Helmut Krcmar,et al. Big Data , 2014, Wirtschaftsinf..
[7] N. Denton,et al. The Dimensions of Residential Segregation , 1988 .
[8] N. Eagle,et al. Network Diversity and Economic Development , 2010, Science.
[9] Tijs Neutens,et al. The Social Interaction Potential of Metropolitan Regions: A Time-Geographic Measurement Approach Using Joint Accessibility , 2013 .
[10] P. Olivier,et al. Socio-Geography of Human Mobility: A Study Using Longitudinal Mobile Phone Data , 2012, PloS one.
[11] Teresa P. R. Caldeira. Fortified Enclaves: The New Urban Segregation , 1996, Cities and Citizenship.
[12] O. Bonin,et al. Commuting patterns in the metropolitan region of Rio de Janeiro. What differences between formal and informal jobs , 2016 .
[13] M. Barthelemy,et al. From mobile phone data to the spatial structure of cities , 2014, Scientific Reports.
[14] A-L Barabási,et al. Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.
[15] Joseph Ferreira,et al. Activity-Based Human Mobility Patterns Inferred from Mobile Phone Data: A Case Study of Singapore , 2017, IEEE Transactions on Big Data.
[16] Albert-László Barabási,et al. Limits of Predictability in Human Mobility , 2010, Science.
[17] Marc Barthelemy,et al. Is spatial information in ICT data reliable? , 2016, ArXiv.
[18] N. Krieger. Embodying Inequality: A Review of Concepts, Measures, and Methods for Studying Health Consequences of Discrimination , 1999, International journal of health services : planning, administration, evaluation.
[19] Marcelinus Henry Menori,et al. Residential Segregation , 2019 .
[20] Tanja Hueber,et al. Urban Development: Theory, Fact, and Illusion , 1988 .
[21] W. Powell,et al. SOCIAL COHESION , 2005 .
[22] Tsuyoshi Murata,et al. {m , 1934, ACML.
[23] Luis Mario Floría,et al. Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes , 2016, Royal Society Open Science.
[24] G. Duranton,et al. Micro-Foundations of Urban Agglomeration Economies , 2003 .
[25] W. Wilson,et al. The Truly Disadvantaged: The Inner City, The Underclass, and Public Policy. , 1988 .
[26] A. Wilson. in the Theory of Trip Distribution, Mode Split and Route Split , 2016 .
[27] A. Kearns,et al. Social Cohesion, Social Capital and the Neighbourhood , 2001 .
[28] Maxime Lenormand,et al. Immigrant community integration in world cities , 2016, PloS one.
[29] Enrique Frías-Martínez,et al. Comparing and modelling land use organization in cities , 2015, Royal Society Open Science.
[30] Boris Sotomayor-Gómez,et al. City limits in the age of smartphones and urban scaling , 2020, Comput. Environ. Urban Syst..
[31] Zbigniew Smoreda,et al. Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models , 2017, Royal Society Open Science.
[32] William Julius Wilson. The Truly Disadvantaged: The Inner City, the Underclass, and Public Policy, Second Edition , 2012 .
[33] Vincent D. Blondel,et al. A survey of results on mobile phone datasets analysis , 2015, EPJ Data Science.
[34] J. Ruiz-Tagle. A Theory of Socio-spatial Integration: Problems, Policies and Concepts from a US Perspective , 2013 .
[35] Ciro Cattuto,et al. Shopping mall attraction and social mixing at a city scale , 2018, EPJ Data Science.
[36] Gabriel Cadamuro,et al. Predicting poverty and wealth from mobile phone metadata , 2015, Science.
[37] Gilles Duranton,et al. Chapter 48 – Micro-Foundations of Urban Agglomeration Economies , 2004 .
[38] Torsten Hägerstraand. WHAT ABOUT PEOPLE IN REGIONAL SCIENCE , 1970 .
[39] K. Axhausen,et al. Activity spaces: Measures of social exclusion? , 2003 .
[40] K. Axhausen,et al. Activity spaces: Measures of social exclusion? , 2003 .
[41] T. Hägerstrand. What about people in Regional Science? , 1970 .
[42] Zbigniew Smoreda,et al. Comparing Regional Patterns of Individual Movement Using Corrected Mobility Entropy , 2018 .
[43] S. Leitão,et al. O plano de mobilidade urbana e o futuro das cidades , 2013 .
[44] Zbigniew Smoreda,et al. Using big data to study the link between human mobility and socio-economic development , 2015, 2015 IEEE International Conference on Big Data (Big Data).
[45] H. Madsen,et al. Cities , 2009 .
[46] Sandra Luque,et al. Multiscale socio-ecological networks in the age of information , 2018, PloS one.
[47] Vinicius M. Netto,et al. Cities, from Information to Interaction , 2018, Entropy.
[48] Francisco Sabatini,et al. The Social Spatial Segregation in the Cities of Latin America , 2006 .
[49] Paul A. Jargowsky,et al. Poverty and Place: Ghettos, Barrios, and the American City , 1998 .
[50] Marta C. González,et al. The path most traveled: Travel demand estimation using big data resources , 2015, Transportation Research Part C: Emerging Technologies.
[51] M. Barthelemy,et al. Human mobility: Models and applications , 2017, 1710.00004.
[52] Maxime Lenormand,et al. Crowdsourcing the Robin Hood effect in cities , 2016, Appl. Netw. Sci..
[53] Carlo Ratti,et al. Human mobility and socioeconomic status: Analysis of Singapore and Boston , 2018, Comput. Environ. Urban Syst..
[54] Tijs Neutens,et al. Measuring Segregation Using Patterns of Daily Travel Behavior: A Social Interaction-Based Model of Exposure , 2015 .
[55] Athanasios V. Vasilakos,et al. Big data: From beginning to future , 2016, Int. J. Inf. Manag..
[56] Nugraha P. Utama,et al. Residential Segregation , 2019, 2019 International Conference of Advanced Informatics: Concepts, Theory and Applications (ICAICTA).
[57] E. Glaeser,et al. Are Ghettos Good or Bad? , 1995 .
[58] Maarten Vanhoof,et al. Mobile Phone Indicators and Their Relation to the Socioeconomic Organisation of Cities , 2018, ISPRS Int. J. Geo Inf..
[59] Matias Garreton,et al. Identifying an optimal analysis level in multiscalar regionalization: A study case of social distress in Greater Santiago , 2016, Comput. Environ. Urban Syst..
[60] M. Barthelemy,et al. Patterns of Residential Segregation , 2015, PloS one.
[61] D. Massey. American Apartheid: Segregation and the Making of the Underclass , 1990, American Journal of Sociology.
[62] G. G. Stokes. "J." , 1890, The New Yale Book of Quotations.
[63] C. Flores. Residential segregation and the geography of opportunities: A spatial analysis of heterogeneity and spillovers in education , 2008 .
[64] Wen-Jing Hsu,et al. Predictability of individuals' mobility with high-resolution positioning data , 2012, UbiComp.
[65] R. Kempen,et al. On the social significance of spatial location; Spatial segregation and social inclusion , 1998 .
[66] Luís M. A. Bettencourt,et al. Professional diversity and the productivity of cities , 2012, Scientific Reports.
[67] Emmanuel Saez,et al. World inequality report 2018 , 2018 .