Borja Moya-Gómez
Biographic Data
| ID | 6306281 |
|---|---|
| NAME | Borja Moya-Gómez |
| GIVEN NAMES | Borja |
| FAMILY NAME | Moya-Gómez |
| SIGNATURE | MOYA-GÓMEZ B |
| AFFILIATIONS | Universidad Complutense de Madrid |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 25 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Using mobile phone data to explore gender and age gaps in urban mobility. Revealing the changes after Covid-19 in the metropolitan region of Madrid (Spain)
Gender differences in mobility are common in cities but analyzing them using data from travel surveys is limited by the sample size and the lack of detailed spatial and temporal patterns for different population groups. Big data sources, such as mobile phone data, offer almost ubiquitous data of daily mobility patterns and their changes while including basic socio-demographic characteristics. This paper studies differences in urban mobility from …
Light in the darkness
City nightlife supports a significant part of our social interactions, enhancing social wellbeing and community-building dynamics. COVID-19 impact on nightlife has been particularly dramatic and expanded over time. Few studies have analyzed this impact, and nightlife recovery remains even less explored. This study examines the post-COVID-19 recovery of nightlife using mobile phone data in Kyoto (Japan) and Madrid (Spain), two cities with differen…
Exploring night and day socio-spatial segregation based on mobile phone data
Social segregation research has a long tradition in urban studies. Usually, these studies focus on the residential dimension, using official registries (e.g., census data), which show population distribution at night. Nevertheless, these studies disregard the fact that the population in cities is highly mobile, and its spatial distribution dramatically changes between night and day. The emergence of new data sources (Big Data) creates perfect con…
The city turned off
Due to the rapid expansion of the COVID-19 pandemic, many countries ordained lockdowns, establishing different restrictions on people's mobility. Exploring to what extent these measures have been effective is critical in order to better respond to similar future scenarios. This article uses anonymous mobile phone data to study the impact of the Spanish lockdown on the daily dynamics of the Madrid metropolitan area (Spain). The analysis has been c…
Tourists' digital footprint in cities
Tourists' digital footprint in cities
Exploring night and day socio-spatial segregation based on mobile phone data
Social segregation research has a long tradition in urban studies. Usually, these studies focus on the residential dimension, using official registries (e.g., census data), which show population distribution at night. Nevertheless, these studies disregard the fact that the population in cities is highly mobile, and its spatial distribution dramatically changes between night and day. The emergence of new data sources (Big Data) creates perfect con…
The city turned off
Due to the rapid expansion of the COVID-19 pandemic, many countries ordained lockdowns, establishing different restrictions on people's mobility. Exploring to what extent these measures have been effective is critical in order to better respond to similar future scenarios. This article uses anonymous mobile phone data to study the impact of the Spanish lockdown on the daily dynamics of the Madrid metropolitan area (Spain). The analysis has been c…
Light in the darkness
City nightlife supports a significant part of our social interactions, enhancing social wellbeing and community-building dynamics. COVID-19 impact on nightlife has been particularly dramatic and expanded over time. Few studies have analyzed this impact, and nightlife recovery remains even less explored. This study examines the post-COVID-19 recovery of nightlife using mobile phone data in Kyoto (Japan) and Madrid (Spain), two cities with differen…
Using mobile phone data to explore gender and age gaps in urban mobility. Revealing the changes after Covid-19 in the metropolitan region of Madrid (Spain)
Gender differences in mobility are common in cities but analyzing them using data from travel surveys is limited by the sample size and the lack of detailed spatial and temporal patterns for different population groups. Big data sources, such as mobile phone data, offer almost ubiquitous data of daily mobility patterns and their changes while including basic socio-demographic characteristics. This paper studies differences in urban mobility from …
Geography (4 works) · Mobile phone (4 works) · Computer Science (3 works) · Human Mobility and Location-Based Analysis (3 works) · Phone (3 works) · Population (3 works) · Sociology (3 works) · Urban Transport and Accessibility (3 works) · Advertising (2 works) · Business (2 works)