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Geo-Located Tweets. Enhancing Mobility Maps and Capturing Cross-Border Movement.

PLoS ONE(2015)SCI 3区

Penn State Univ

Cited 101|Views30
Abstract
Capturing human movement patterns across political borders is difficult and this difficulty highlights the need to investigate alternative data streams. With the advent of smart phones and the ability to attach accurate coordinates to Twitter messages, users leave a geographic digital footprint of their movement when posting tweets. In this study we analyzed 10 months of geo-located tweets for Kenya and were able to capture movement of people at different temporal (daily to periodic) and spatial (local, national to international) scales. We were also able to capture both long and short distances travelled, highlighting regional connections and cross-border movement between Kenya and the surrounding countries. The findings from this study has broad implications for studying movement patterns and mapping inter/intra-region movement dynamics.
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要点】:该论文利用带有地理坐标的推文数据,研究了肯尼亚地区10个月的人类移动模式,为捕捉跨国界移动提供了新的数据流,增强了流动性地图,并捕捉了跨政治边界的移动模式。

方法】:研究者分析了带有地理坐标的肯尼亚推文数据,以追踪人们在不同的时间和空间尺度上的移动。

实验】:实验使用肯尼亚的地理定位推文数据集,分析了从日常到定期的、从地方到国际的空间和时间尺度的移动,结果表明可以捕捉到长距离和短距离的移动,并突显了地区间的联系和肯尼亚与其邻国之间的跨境移动。