Insiders and outsiders: comparing urban impressions between population groups

"There is a growing interest in social and urban computing to employ crowdsourcing as means to gather impressions of urban perception for indoor and outdoor environments. Previous studies have established that reliable estimates of urban perception can be obtained using online crowdsourcing sys...

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Detalles Bibliográficos
Autores: Darshan Santani, SALVADOR RUIZ CORREA, DANIEL GATICA PEREZ
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2017
País:México
Institución:Instituto Potosino de Investigación Científica y Tecnológica
Repositorio:Repositorio Institucional del IPICYT
OAI Identifier:oai:ipicyt.repositorioinstitucional.mx:1010/2182
Acceso en línea:http://ipicyt.repositorioinstitucional.mx/jspui/handle/1010/2182
Access Level:acceso abierto
Palabra clave:info:eu-repo/classification/cti/7
Descripción
Sumario:"There is a growing interest in social and urban computing to employ crowdsourcing as means to gather impressions of urban perception for indoor and outdoor environments. Previous studies have established that reliable estimates of urban perception can be obtained using online crowdsourcing systems, but implicitly assumed that the judgments provided by the crowd are not dependent on the background knowledge of the observer. In this paper, we investigate how the impressions of outdoor urban spaces judged by online crowd annotators, compare with the impressions elicited by the local inhabitants, along six physical and psychological labels. We focus our study in a developing city where understanding and characterization of these socio-urban perceptions is of societal importance. We found statistically significant differences between the two population groups. Locals perceived places to be more dangerous and dirty, when compared with online crowd workers; while online annotators judged places to be more interesting in comparison to locals. Our results highlight the importance of the degree of familiarity with urban spaces and background knowledge while rating urban perceptions, which is lacking in some of the existing work in urban computing."