| Title |
Linking Geosocial Sensing with the Socio-Demographic Fabric of Smart Cities |
| ID_Doc |
42101 |
| Authors |
Ostermann, FO |
| Title |
Linking Geosocial Sensing with the Socio-Demographic Fabric of Smart Cities |
| Year |
2021 |
| Published |
Isprs International Journal Of Geo-Information, 10, 2 |
| DOI |
10.3390/ijgi10020052 |
| Abstract |
Technological advances have enabled new sources of geoinformation, such as geosocial media, and have supported the propagation of the concept of smart cities. This paper argues that a city cannot be smart without citizens in the loop, and that a geosocial sensor might be one component to achieve that. First, we need to better understand which facets of urban life could be detected by a geosocial sensor, and how to calibrate it. This requires replicable studies that foster longitudinal and comparative research. Consequently, this paper examines the relationship between geosocial media content and socio-demographic census data for a global city, London, at two administrative levels. It aims for a transparent study design to encourage replication, using Term Frequency-Inverse Document Frequency of keywords, rule-based and word-embedding sentiment analysis, and local cluster analysis. The findings of limited links between geosocial media content and socio-demographic characteristics support earlier critiques on the utility of geosocial media for smart city planning purposes. The paper concludes that passive listening to publicly available geosocial media, in contrast to pro-active engagement with citizens, seems of limited use to understand and improve urban quality of life. |
| Author Keywords |
geosocial media; user-generated geographic content; smart city; smart citizen; social sensing; replication; reproducibility |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000622598500001 |
| WoS Category |
Computer Science, Information Systems; Geography, Physical; Remote Sensing |
| Research Area |
Computer Science; Physical Geography; Remote Sensing |
| PDF |
https://www.mdpi.com/2220-9964/10/2/52/pdf?version=1611736377
|