Automating a framework to extract and analyse transport related social media content: The potential and the challenges

Kuflik, T, Minkov, E, Nocera, S et al. (3 more authors) (2017) Automating a framework to extract and analyse transport related social media content: The potential and the challenges. Transportation Research Part C: Emerging Technologies, 77. pp. 275-291. ISSN 0968-090X

Abstract

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Authors/Creators:
  • Kuflik, T
  • Minkov, E
  • Nocera, S
  • Grant-Muller, S
  • Gal-Tzur, A
  • Shoor, I
Copyright, Publisher and Additional Information: (c) 2017, Elsevier. This is an author produced version of a paper published in Transportation Research Part C: Emerging Technologies. Uploaded in accordance with the publisher's self-archiving policy
Keywords: Mining Twitter for transport information; Social media; Text mining; Opinion mining; Twitter
Dates:
  • Accepted: 2 February 2017
  • Published (online): 16 February 2017
  • Published: April 2017
Institution: The University of Leeds
Depositing User: Symplectic Publications
Date Deposited: 11 May 2017 11:15
Last Modified: 03 Mar 2020 10:34
Published Version: https://doi.org/10.1016/j.trc.2017.02.003
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.trc.2017.02.003

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