Abstract

Locative social media networks as open sources of data allow researchers and professionals to acknowledge which city places are preferred, used and livable. Following this hypothesis, this paper proposes a methodology to identify successful public spaces – plazas – through the location-based social media network Foursquare and to analyze their urban position using morphological and historical cartographies.The overall methodology comprises three stages. First, the most important cities of the province of Alicante were selected. Second, the most relevant plaza of each city was identified using data retrieved from the social network Foursquare. Finally, the location of each plaza is analyzed in relation to the historic center and the main axes of the city. Possible correlations between their urban location and their vibrant character were subsequently identified.Two findings have emerged from this study: (a) a strong spatial relationship exists between the most successful plazas and the historic city center, which reinforces their traditional social character; and (b) all plazas share two similar traits, their location within the urban network and their proximity to the main axes of the city.

Highlights

  • City spaces have traditionally functioned as places for social interaction and cultural representation

  • The retrieved data from the Foursquare search consisted of public space related to venues that could be ranked by social relevance using the cumulative visitors' figures - Table 2

  • Except in the case of Alcoy, the results showed an important difference between the plazas ranked #1 and #2

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Summary

Introduction

City spaces have traditionally functioned as places for social interaction and cultural representation. Face-to-face encounters among strangers and friends are highly dependent on online relationships (Gaspar & Glaeser, 1996; Moss, 1998) This situation urges the recognition of socially accepted public spaces as a crucial matter for urban planners and designers. Given that there is ample information available online, it is possible to identify which spaces are preferred over others and study their characteristics with a view to learning from them This will aid the assessment of future decision-making processes related to urban systems (Agryzkov, Martí, Tortosa, & Vicent, 2016; Calabrese, Ferrari, & Blondel, 2014; Ruíz Sánchez, 2012)

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