论文标题
智能城市中的微型行为:通过大型社交数据仔细观察共享的码头电子示波器
Micromobility in Smart Cities: A Closer Look at Shared Dockless E-Scooters via Big Social Data
论文作者
论文摘要
在城市地区,微型行为正在塑造第一英里和最后一英里的旅行。最近,由于负担能力,通过应用程序易于访问性和零排放,共享的无码电动踏板车(电子驾驶员)已成为大城市短途通勤者驾驶的每日替代品。同时,电子驾驶员在城市管理中面临挑战,例如交通规则,公共安全,停车法规和责任问题。在本文中,我们收集并调查了580万个踏板车标签的推文和144,197张图像,该图像由270万用户从2018年10月到2020年3月,通过众包数据分析仔细研究了共享的电子磁带。我们从时空的角度介绍了电子驾驶员的用法,探讨了不同的业务角色(即骑手,演出工人和乘车公司),检查了操作模式(例如伤害类型和停车行为),并进行了情感分析。据我们所知,本文是使用大型社交数据对共享电子示威者进行的首次大规模系统研究。
The micromobility is shaping first- and last-mile travels in urban areas. Recently, shared dockless electric scooters (e-scooters) have emerged as a daily alternative to driving for short-distance commuters in large cities due to the affordability, easy accessibility via an app, and zero emissions. Meanwhile, e-scooters come with challenges in city management, such as traffic rules, public safety, parking regulations, and liability issues. In this paper, we collected and investigated 5.8 million scooter-tagged tweets and 144,197 images, generated by 2.7 million users from October 2018 to March 2020, to take a closer look at shared e-scooters via crowdsourcing data analytics. We profiled e-scooter usages from spatial-temporal perspectives, explored different business roles (i.e., riders, gig workers, and ridesharing companies), examined operation patterns (e.g., injury types, and parking behaviors), and conducted sentiment analysis. To our best knowledge, this paper is the first large-scale systematic study on shared e-scooters using big social data.