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Investigating social media spatiotemporal transferability for transport

Chaniotakis, E; Abouelela, M; Antoniou, C; Goulias, K; (2022) Investigating social media spatiotemporal transferability for transport. Communications in Transportation Research , 2 , Article 100081. 10.1016/j.commtr.2022.100081. Green open access

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Abstract

Social Media have increasingly provided data about the movement of people in cities making them useful in understanding the daily life of people in different geographies. Particularly useful for travel analysis is when Social Media users allow (voluntarily or not) tracing their movement using geotagged information of their communication with these online platforms. In this paper we use geotagged tweets from 10 cities in the European Union and United States of America to extract spatiotemporal patterns, study differences and commonalities among these cities, and explore the nature of user location recurrence. The analysis here shows the distinction between residents and tourists is fundamental for the development of city-wide models. Identification of repeated rates of location (recurrence) can be used to define activity spaces. Differences and similarities across different geographies emerge from this analysis in terms of local distributions but also in terms of the worldwide reach among the cities explored here. The comparison of the temporal signature between geotagged and non-geotagged tweets also shows similar temporal distributions that capture in essence city rhythms of tweets and activity spaces.

Type: Article
Title: Investigating social media spatiotemporal transferability for transport
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.commtr.2022.100081
Publisher version: https://doi.org/10.1016/j.commtr.2022.100081
Language: English
Additional information: © 2022 The Author(s). Published by Elsevier Ltd on behalf of Tsinghua University Press. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Social media, Data transferability, Transport modelling, International comparisons
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10157091
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