Caracterização da relação entre redes sociais e mobilidade de indivíduos em contextos urbanos
Resumo
A compreensão da organização urbana é fundamental para um melhor planejamento e definição de políticas públicas que visem maior bem estar da população e mitigação de problemas sociais. Modelos computacionais capazes de integrar dados de diferentes fontes podem auxiliar a caracterização da complexa organização geográfica e socioeconômica da população em áreas urbanas com grande resolução e aplicabilidade em contextos práticos. Este trabalho apresenta a análise da complexidade urbana representada pelas relações sociais e de mobilidade através da investigação de registros de ligações telefônicas armazenadas como Call Detail Records (CDR). Considerando duas cidades com características distintas, experimentos realizados a partir da caracterização da mobilidade individual das pessoas permitem observar uma forte interedependência entre seu comportamento de mobilidade no espaço urbano e o comportamento exibido pelas pessoas que definem sua rede social.
Palavras-chave:
Dados CDR, rede social, padrões de mobilidade, dados de telefonia móvel
Referências
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Barbosa, H., Barthelemy, M., Ghoshal, G., James, C. R., Lenormand, M., Louail, T.,Menezes, R., Ramasco, J. J., Simini, F., and Tomasini, M. (2018). Human mobility:Models and applications.Physics Reports, 734:1–74.
Blondel, V. D., Decuyper, A., and Krings, G. (2015). A survey of results on mobile phonedatasets analysis. EPJ Data Science, 4:1–55.
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., and Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Stat. Mech., 2008(10):P10008.
Cherifi, H., Palla, G., Szymanski, B. K., and Lu, X. (2019). On community structure incomplex networks: challenges and opportunities. Applied Network Science, 4(117).
Cornacchia, G., Rossetti, G., and Pappalardo, L. (2020). Modelling human mobility considering spatial,temporal and social dimensions.arXiv:2007.02371.
Gonzalez, M. C., Hidalgo, C. A., and Barabasi, A.-L. (2008). Understanding individualhuman mobility patterns. Nature, 453(7196):779–782.
Grabowicz, P. A., Ramasco, J. J., Gonçalves, B., and Eguíluz, V. M. (2014). Entangling mobility and interactions in social media. PLOS ONE, 9(3):1–12.
Kovanen, L., Saramaki, J., and Kaski, K. (2010). Reciprocity of mobile phone calls. arXiv: Physics and Society.
Lenormand, M. and Ramasco, J. J. (2016). Towards a better understanding of cities usingmobility data. Built Environment, 42:356–364(9).
Mac Carron, P., Kaski, K., and Dunbar, R. (2016). Calling dunbar’s numbers. Social Networks, 47:151–155.
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., and Galstyan, A. (2019). A survey on bias and fairness in machine learning. CoRR, abs/1908.09635.
Newman, M. and Park, J. (2003). Why social networks are different than other types of networks. Physical review. E, 68:036122.
Onnela, J.-P., Saramaki, J., Hyvonen, J., Szabó, G., Lazer, D., Kaski, K., Kertész, J., and Barabási, A.-L. (2007). Structure and tie strengths in mobile communication networks. PNAS, 104:7332–6.
Sapiezynski, P., Stopczynski, A., Gatej, R., and Lehmann, S. (2015). Tracking humanmobility using wifi signals. PLOS ONE, 10(7):1–11.
Tibély, G., Kovanen, L., Karsai, M., Kaski, K., Kertész, J., and Saramaki, J. (2011).Communities and beyond: Mesoscopic analysis of a large social network with complementary methods. Physical Review E, 83(5).
Toole, J. L., Herrera-Yaque, C., Schneider, C. M., and González, M. C. (2015). Coupling human mobility and social ties. 12(105):20141128.
Vieira, V. F., Xavier, C. R., and Evsukoff, A. G. (2020). A comparative study of overlapping community detection methods from the perspective of the structural properties. Appl. Netw. Sci., 5(1):51.
Wang, C., Strathman, A., Lizardo, O., Hachen, D., Toroczkai, Z., and Chawla, N. (2011).Weighted reciprocity in human communication networks.
Barbosa, H., Barthelemy, M., Ghoshal, G., James, C. R., Lenormand, M., Louail, T.,Menezes, R., Ramasco, J. J., Simini, F., and Tomasini, M. (2018). Human mobility:Models and applications.Physics Reports, 734:1–74.
Blondel, V. D., Decuyper, A., and Krings, G. (2015). A survey of results on mobile phonedatasets analysis. EPJ Data Science, 4:1–55.
Blondel, V. D., Guillaume, J.-L., Lambiotte, R., and Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Stat. Mech., 2008(10):P10008.
Cherifi, H., Palla, G., Szymanski, B. K., and Lu, X. (2019). On community structure incomplex networks: challenges and opportunities. Applied Network Science, 4(117).
Cornacchia, G., Rossetti, G., and Pappalardo, L. (2020). Modelling human mobility considering spatial,temporal and social dimensions.arXiv:2007.02371.
Gonzalez, M. C., Hidalgo, C. A., and Barabasi, A.-L. (2008). Understanding individualhuman mobility patterns. Nature, 453(7196):779–782.
Grabowicz, P. A., Ramasco, J. J., Gonçalves, B., and Eguíluz, V. M. (2014). Entangling mobility and interactions in social media. PLOS ONE, 9(3):1–12.
Kovanen, L., Saramaki, J., and Kaski, K. (2010). Reciprocity of mobile phone calls. arXiv: Physics and Society.
Lenormand, M. and Ramasco, J. J. (2016). Towards a better understanding of cities usingmobility data. Built Environment, 42:356–364(9).
Mac Carron, P., Kaski, K., and Dunbar, R. (2016). Calling dunbar’s numbers. Social Networks, 47:151–155.
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., and Galstyan, A. (2019). A survey on bias and fairness in machine learning. CoRR, abs/1908.09635.
Newman, M. and Park, J. (2003). Why social networks are different than other types of networks. Physical review. E, 68:036122.
Onnela, J.-P., Saramaki, J., Hyvonen, J., Szabó, G., Lazer, D., Kaski, K., Kertész, J., and Barabási, A.-L. (2007). Structure and tie strengths in mobile communication networks. PNAS, 104:7332–6.
Sapiezynski, P., Stopczynski, A., Gatej, R., and Lehmann, S. (2015). Tracking humanmobility using wifi signals. PLOS ONE, 10(7):1–11.
Tibély, G., Kovanen, L., Karsai, M., Kaski, K., Kertész, J., and Saramaki, J. (2011).Communities and beyond: Mesoscopic analysis of a large social network with complementary methods. Physical Review E, 83(5).
Toole, J. L., Herrera-Yaque, C., Schneider, C. M., and González, M. C. (2015). Coupling human mobility and social ties. 12(105):20141128.
Vieira, V. F., Xavier, C. R., and Evsukoff, A. G. (2020). A comparative study of overlapping community detection methods from the perspective of the structural properties. Appl. Netw. Sci., 5(1):51.
Wang, C., Strathman, A., Lizardo, O., Hachen, D., Toroczkai, Z., and Chawla, N. (2011).Weighted reciprocity in human communication networks.
Publicado
18/07/2021
Como Citar
RIBEIRO, José Mauro; ALENCAR, Ricardo; MARTINS, Gustavo; XAVIER, Carolina; EVSUKOFF, Alexandre; VIEIRA, Vinícius.
Caracterização da relação entre redes sociais e mobilidade de indivíduos em contextos urbanos. In: BRAZILIAN WORKSHOP ON SOCIAL NETWORK ANALYSIS AND MINING (BRASNAM), 10. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 32-43.
ISSN 2595-6094.
DOI: https://doi.org/10.5753/brasnam.2021.16123.
