Design a Sustainable Micro-mobility Future: Trends and Challenges in the United States and European Union Using Natural Language Processing Techniques
Lilit Avetisyan, Chengxin Zhang, Sue Bai, Ehsan Moradi Pari, Fred, Feng, Shan Bao, Feng Zhou

TL;DR
This study analyzes Twitter data using NLP techniques to understand public opinions on micro-mobility in the US and EU, revealing regional differences in attitudes, usage, and concerns to inform sustainable urban transportation planning.
Contribution
It applies advanced NLP methods to categorize and compare micro-mobility opinions across regions, providing new insights into public perceptions and challenges.
Findings
EU has more positive opinions than the US.
Micro-mobility is used more for recreation and utilitarian purposes in the EU.
US users express more concerns about infrastructure and regulation.
Abstract
Micro-mobility is promising to contribute to sustainable cities in the future with its efficiency and low cost. To better design such a sustainable future, it is necessary to understand the trends and challenges. Thus, we examined people's opinions on micro-mobility in the US and the EU using Tweets. We used topic modeling based on advanced natural language processing techniques and categorized the data into seven topics: promotion and service, mobility, technical features, acceptance, recreation, infrastructure and regulations. Furthermore, using sentiment analysis, we investigated people's positive and negative attitudes towards specific aspects of these topics and compared the patterns of the trends and challenges in the US and the EU. We found that 1) promotion and service included the majority of Twitter discussions in the both regions, 2) the EU had more positive opinions than the…
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Taxonomy
TopicsHuman Mobility and Location-Based Analysis · Urban Transport and Accessibility · Urban and Freight Transport Logistics
Methodstravel james
