Big data for big issues
Revealing travel patterns of low-income population based on smart card data mining in a global south unequal city
Dados Bibliográficos
| ID | 12296154 |
|---|---|
| Autores | Caio Pieroni (Universidade de São Paulo, autor correspondente), Mariana Giannotti (0000-0002-7024-8015, Universidade de São Paulo), Bianca Bianchi Alves (World Bank Group), Renato Arbex (0000-0003-0186-3855, Universidade de São Paulo) |
| Ano | 2021 |
| Volume | 96 |
| Páginas | 103203-103203 |
| Data de publicação | 2021-10-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Journal of Transport Geography (JOURNAL) |
| Identificadores do periódico | ISSN: 0966-6923 • E-ISSN: 1873-1236 |
| Editora | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.jtrangeo.2021.103203 |
| OpenAlex | W3201899217 |
| Idioma | EN |
| Citações recebidas | 12 |
| Referências citadas | 37 |
Big data · Business · Cluster analysis · Computer security · Data mining · DBSCAN · Demographic economics · Economics · Geography · Human settlement · Low income · Payment · Population · Residence · Settlement (finance · Smart card · Sociology · Transport engineering · Travel behavior · Computer Science · Demography · Engineering · Human Mobility and Location-Based Analysis · Transportation and Mobility Innovations · Urban Transport and Accessibility · Finance
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| Obras citantes distintas | 12 |
|---|---|
| Citações por ano | 3 |
| Intervalo de citações | 2022 - 2026 (5) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 12 |