Using Georeferenced Twitter Data to Estimate Pedestrian Traffic in an Urban Road Network

Debjit Bhowmick, Stephan Winter, Mark Stevenson

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

Abstract

Since existing methods to estimate the pedestrian activity in an urban area are data-intensive, we ask the question whether just georeferenced Twitter data can be a viable proxy for inferring pedestrian activity. Walking is often the mode of the last leg reaching an activity location, from where, presumably, the tweets originate. This study analyses this question in three steps. First, we use correlation analysis to assess whether georeferenced Twitter data can be used as a viable proxy for inferring pedestrian activity. Then we adopt standard regression analysis to estimate pedestrian traffic at existing pedestrian sensor locations using georeferenced tweets alone. Thirdly, exploiting the results above, we estimate the hourly pedestrian traffic counts at every segment of the study area network for every hour of every day of the week. Results show a fair correlation between tweets and pedestrian counts, in contrast to counts of other modes of travelling. Thus, this method contributes a non-data-intensive approach for estimating pedestrian activity. Since Twitter is an omnipresent, publicly available data source, this study transcends the boundaries of geographic transferability and scalability, unlike its more traditional counterparts.

Original languageEnglish
Title of host publication11th International Conference on Geographic Information Science
Subtitle of host publicationGIScience 2021, September 27–30, 2021, Poznań, Poland Part I
EditorsKrzysztof Janowicz, Judith A. Verstegen
Place of PublicationGermany
PublisherSchloss Dagstuhl
Number of pages15
ISBN (Electronic)9783959771665
DOIs
Publication statusPublished - 25 Sep 2020
Externally publishedYes
EventInternational Conference on Geographic Information Science, GIScience 2021 - Poznan, Poland
Duration: 27 Sep 202130 Sep 2021
Conference number: 11th
https://dblp.org/db/conf/giscience/giscience2021-1.html

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume177
ISSN (Print)1868-8969

Conference

ConferenceInternational Conference on Geographic Information Science, GIScience 2021
Abbreviated titleGIScience 2021
Country/TerritoryPoland
CityPoznan
Period27/09/2130/09/21
Internet address

Keywords

  • correlation analysis
  • location-based
  • pedestrian traffic
  • regression analysis
  • Twitter

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