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. 2023 Jan:132:104094.
doi: 10.1016/j.cities.2022.104094. Epub 2022 Nov 10.

Contesting views on mobility restrictions in urban green spaces amid COVID-19-Insights from Twitter in Latin America and Spain

Jaime Sainz-Santamaria  1 , Daniela Moctezuma  2 , Adan L Martinez-Cruz  3 , Eric S Téllez  4 , Mario Graff  4 , Sabino Miranda-Jiménez  4
Affiliations

Contesting views on mobility restrictions in urban green spaces amid COVID-19-Insights from Twitter in Latin America and Spain

Jaime Sainz-Santamaria et al. Cities. 2023 Jan.

Abstract

Positive sentiments towards urban green spaces (UGS) unequivocally increased worldwide amid COVID-19. In contrast, this paper documents that views on mobility restrictions applicable to UGS are of a contested nature. That is, while residents unambiguously report positive sentiments towards UGS, they do not share views on how to administer access to UGS-which is a matter of public policy. These contesting views reflect opposite demands that managers of UGS had to balance during the pandemic as they faced the challenge of reducing risk of spread while providing services that support physical and mental health of residents. The empirical analysis in this paper relies on views inferred through a text classification algorithm implemented on Twitter messages posted from January to October 2020, by urban residents in three Latin American countries-Argentina, Colombia, and Mexico-and Spain. The focus on Latin America is motivated by the documented lack of compliance with mobility restrictions; Spain works as a comparison point to learn differences with respect to other regions. Understanding and following in real-time the evolution of contesting views amid a pandemic is useful for managers and city planners to inform adaptation measures-e.g. communication strategies can be tailored to residents with specific views.

Keywords: COVID-19; Latin America; Mobility restrictions; Twitter; Urban green spaces; Views.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Workflow for the methodology proposed.
Fig. 2
Fig. 2
Distribution of our working sample by country, before and after the classification process.
Fig. 3
Fig. 3
Distribution of working dataset, by topics and country.
Fig. 4
Fig. 4
Point geolocated tweets from our working dataset over some main cities and metropolitan areas in Mexico.
Fig. 5
Fig. 5
Evolution of number of tweets by view on a weekly basis—dotted vertical lines denote week that a first directive on mobility restrictions was issued and subsequent weeks that mobility restrictions were strengthened; straight vertical lines denote weeks that restrictions were officially softened.
Fig. 6
Fig. 6
Frequency of tweets across country, by topic and view. Note: D-UGS: Demand for UGS; D-NC: Denounce for non-compliance.
Fig. 7
Fig. 7
Evolution of stringency of mobility restriction and percentage of tweets denouncing non-compliance on a weekly basis.
Fig. 8
Fig. 8
Evolution of trend of percentage of tweets denouncing non-compliance on a weekly basis—estimates have resulted from fitting 20-period rolling window OLS specifications for percentage of tweets denouncing non-compliance as a function of stringency of mobility restriction and a trend term.
Fig. 9
Fig. 9
Evolution of partial correlation between stringency in mobility restrictions and percentage of tweets denouncing non-compliance on a weekly basis—estimates have resulted from fitting 20-period rolling window OLS specifications for percentage of tweets denouncing non-compliance as a function of stringency of mobility restriction and a trend term.
See this image and copyright information in PMC

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