A text mining approach to elicit public perception of bike-sharing systems

Author:

Kutela Boniphace,Langa Neema,Mwende Sia,Kidando Emmanuel,Kitali Angela E.,Bansal Prateek

Funder

Leverhulme Trust

Publisher

Elsevier BV

Subject

Transportation

Reference26 articles.

1. Open-Ended Versus Closed-Ended Responses: A Comparison Study Using Topic Modeling and Factor Analysis;Baburajan;IEEE Trans. Intell. Transp. Syst.,2020

2. ‘Better Understanding of Factors Influencing Likelihood of Using Shared Bicycle Systems and Frequency of Use’, Transportation Research Record: Journal of the Transportation Research Board;Bachand-Marleau;Transportation Research Board of the National Academies,2012

3. quanteda: An R package for the quantitative analysis of textual data;Benoit;Journal of Open Source Software,2018

4. Blaheta, D. and Johnson, M. (2011) ‘Unsupervised learning of multi-word verbs *’, in Proceedings of the ACL Workshop on Collocations, pp. 54–60.

5. Das, S., Sun, X. and Dutta, A. (2015) ‘Investigating User Ridership Sentiments for Bike Sharing Programs’, Journal of Transportation Technologies. Scientific Research Publishing, Inc, 05(02), pp. 69–75. doi: 10.4236/jtts.2015.52007.

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