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Where to catch ‘em all? – a geographic analysis of Pokémon Go locations

机译:哪里都可以抓住它们? –神奇宝贝围棋位置的地理分析

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In 2016, Niantic Labs released Pokémon Go, an augmented reality smartphone game that attracted millions of users worldwide. This game allows users to “catch” Pokémons through their mobile cameras in different geographic locations that often correspond to prominent places. This paper analyzes the distribution of PokéStops, Pokémon gyms, and spawnpoints in selected urban areas of South Florida and Boston. It identifies which socioeconomic variables and land-use categories affect the density of PokéStops, and how PokéStops and gyms cluster relative to each other. Using nearest neighbor analysis, this paper assesses also how actual PokéStop locations are reflected in Yelp’s “PokéStop nearby” attribute. Results show that black and Hispanic neighborhoods are disadvantaged when it comes to crowd-sourced data coverage, that PokéStops occur more frequently in commercial, recreational and touristic sites and around universities, and that PokéStops tend to cluster around gyms. The latter suggests that these point sets were generated by a similar location selection process. To mitigate geographically linked biases, future versions of augmented reality and geo-games should aim to make them equally accessible in all areas, for example by placing extra resources, such as points of interest, in neighborhoods that are currently underrepresented in data coverage.
机译:2016年,Niantic Labs发行了增强现实智能手机游戏《神奇宝贝Go》,吸引了全球数百万用户。该游戏允许用户通过移动摄像头在通常与著名地点相对应的不同地理位置“捕捉”神奇宝贝。本文分析了南佛罗里达和波士顿特定市区的PokéStops,Pokémon体育馆和生成点的分布。它确定了哪些社会经济变量和土地使用类别会影响PokéStops的密度,以及PokéStops和体育馆如何彼此相对聚集。本文使用最近邻分析法,还评估了实际的PokéStop位置如何反映在Yelp的“附近的PokéStop”属性中。结果表明,在涉及人群数据的覆盖范围中,黑人和西班牙裔社区处于不利地位,PokéStops在商业,娱乐和旅游景点以及大学附近的发生频率更高,并且PokéStops倾向于聚集在体育馆附近。后者表明这些点集是通过类似的位置选择过程生成的。为了减轻与地理位置相关的偏见,增强现实和地理游戏的未来版本应旨在使它们在所有区域中均等可用,例如,通过将额外的资源(例如兴趣点)放置在当前数据覆盖率不足的社区中。

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