Public Opinion on Dockless Bike Sharing: A Machine Learning Approach

Ali Rahim Taleqani · Jill Hough · Kendall E. Nygard

47 citations0/0 files storedTransportation Research Record Journal of the Transportation Research Board

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Urban Transport and Accessibility Sentiment Analysis and Opinion Mining Transportation and Mobility Innovations

Abstract

Dockless bike sharing is an emerging paradigm. Like many other technologies, it brings advantages and disadvantages to communities. Further investigation into public opinion will shed light on the impact of this technology on communities and provide input to city authorities for transportation planning. Transportation planning processes can be enhanced by engaging the community through social media technologies. Social media like Twitter, Facebook, and other microblogging media have been used for planning, but have not been extensively evaluated for that purpose. This study examined approximately 32,000 posts on Twitter to assess public opinion on dockless bike-sharing systems. Using a mix of text mining and statistical techniques, we examined relevant posts to determine the sentiment polarity of tweets, the underlying topics in the tweets, and the extent of engagement and impact on the decision-making process. Results given by two different sentiment algorithms show that there is more positive than negative polarity across the algorithms. Also, the findings show that the underlying topics in tweets include electric scooters, private e-hailing companies, and blockage of sidewalks, among others. The results indicate that the dockless shared mobility models are potentially useful in generating participation, but faced substantial technical, analytical, and communication barriers to influencing decision-making.

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References

1985Methods of coping with social desirability bias: A review 2016Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges 2014Planning and Social Media: A Case Study of Public Transit and Stigma on Twitter 2013Mapping the public agenda with topic modeling: The case of the Russian livejournal

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2021Effects of the autonomous vehicle crashes on public perception of the technology 2022Review of bike-sharing system studies using bibliometrics method 2020From shared micro-mobility to shared responsibility: Using crowdsourcing to understand dockless vehicle violations in Austin, Texas 2020Bike-sharing: the good, the bad, and the future 2021Usage behavior and satisfaction analysis of free-floating bicycle sharing system service: Evidence from a Chinese university campus 2019Identification of Enablers and Barriers for Public Bike Share System Adoption using Social Media and Statistical Models 2022Survey of Machine Learning Methods Applied to Urban Mobility 2019Dynamic Feedback Analysis of Influencing Factors and Challenges of Dockless Bike-Sharing Sustainability in China

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