Looking at Cities in Mexico with Crowds

Mobile and social technologies are providing new opportunities to document, characterize, and gather impressions of urban environments. In this paper, we present a study that examines urban perceptions of three cities in central Mexico (Guanajuato, Leon and Silao), which integrates a mobile crowdsourcing framework to collect geo-localized images of urban environments by a local youth community, and an online crowdsourcing platform (Amazon Mechanical Turk) to gather impressions of urban environments along twelve physical and psychological dimensions. Our study resulted in a collection of 7,000 geo-localized images containing outdoor scenes and views of each city's built environment, including touristic, historical, and residential neighbourhoods; and 156,000 individual judgments from MTurk. Statistical analyses show that outdoor environments can be reliably assessed with respect to most urban dimensions by the observers of crowdsourced images. Furthermore, a cross-city statistical analysis shows that outdoor urban places in Guanajuato (a touristic, cultural heritage site) are perceived as more quiet, picturesque and interesting compared to places in Leon and Silao, which are commercial and industrial hubs, respectively. In contrast Silao, is perceived to have lower accessibility than Leon. Finally, we investigate whether the perceptions of urban environments vary across different times of the day and found that places in the evening are perceived as less happy, pleasant and preserved, when compared to the same place in the morning. Through the use of collective action, participatory sensing and mobile crowdsourcing, our study engages citizens to understand socio-urban problems in their communities.

Presented at:
Proceedings of the 2015 Annual Symposium on Computing for Development, London, United Kingdom

 Record created 2015-12-19, last modified 2018-03-17

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