A nationwide dataset of de-identified activity spaces derived from geotagged social media data

IF 2.6 3区 经济学 Q2 ENVIRONMENTAL STUDIES
Ate Poorthuis, Qingqing Chen, Matthew Zook
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引用次数: 0

Abstract

In this article, we present a historical dataset of activity spaces, originally based on publicly posted and geotagged social media sent within the United States from 2012 to 2019. The dataset, which contains approximately 2 million users and 1.2 billion data points, is de-identified and spatially aggregated to enable ethical and broad sharing across the research community. By publishing the dataset, we hope to help researchers to quickly access and filter data to study people’s activity spaces across a range of places. In this article, we first describe the construction and characteristics of this dataset and then highlight certain limitations of the data through an illustrative analysis of potential bias—an important consideration when using data not collected through representative sampling. Our goal is to empower researchers to create novel, insightful research projects of their own design based on this dataset.
全国范围内的去标识化活动空间数据集,数据来源于地理标记的社交媒体数据
在本文中,我们介绍了一个活动空间历史数据集,该数据集最初基于 2012 年至 2019 年期间在美国境内公开发布并带有地理标记的社交媒体。该数据集包含约 200 万用户和 12 亿个数据点,经过去标识化和空间聚合处理,可在研究界进行合乎道德的广泛共享。我们希望通过发布该数据集,帮助研究人员快速访问和筛选数据,以研究人们在各种场所的活动空间。在本文中,我们首先介绍了该数据集的构建和特点,然后通过对潜在偏差的说明性分析强调了数据的某些局限性--这是在使用非代表性抽样收集的数据时需要考虑的重要因素。我们的目标是让研究人员能够在此数据集的基础上创建自己设计的新颖、有洞察力的研究项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
11.40%
发文量
159
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