Social sensing of urban land use based on analysis of Twitter users' mobility patterns

Aiman Soliman, Kiumars Soltani, Junjun Yin, Anand Padmanabhan, Shaowen Wang

Research output: Contribution to journalArticle

Abstract

A number of recent studies showed that digital footprints around built environments, such as geo-located tweets, are promising data sources for characterizing urban land use. However, challenges for achieving this purpose exist due to the volume and unstructured nature of geo-located social media. Previous studies focused on analyzing Twitter data collectively resulting in coarse resolution maps of urban land use. We argue that the complex spatial structure of a large collection of tweets, when viewed through the lens of individual-level human mobility patterns, can be simplified to a series of key locations for each user, which could be used to characterize urban land use at a higher spatial resolution. Contingent issues that could affect our approach, such as Twitter users' biases and tendencies at locations where they tweet the most, were systematically investigated using 39 million geo-located Tweets and two independent datasets of the City of Chicago: 1) travel survey and 2) parcel-level land use map. Our results support that the majority of Twitter users show a preferential return, where their digital traces are clustered around a few key locations. However, we did not find a general relation among users between the ranks of locations for an individual-based on the density of tweets-and their land use types. On the contrary, temporal patterns of tweeting at key locations were found to be coherent among the majority of users and significantly associated with land use types of these locations. Furthermore, we used these temporal patterns to classify key locations into generic land use types with an overall classification accuracy of 0.78. The contribution of our research is twofold: a novel approach to resolving land use types at a higher resolution, and in-depth understanding of Twitter users' location-related and temporal biases, promising to benefit human mobility and urban studies in general.

Original languageEnglish (US)
Pages (from-to)e0181657
JournalPloS one
Volume12
Issue number7
DOIs
StatePublished - Jan 1 2017

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Land use
land use
Social Media
Information Storage and Retrieval
Lenses
Research
social networks
Lens
travel
Surveys and Questionnaires
Datasets

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Social sensing of urban land use based on analysis of Twitter users' mobility patterns. / Soliman, Aiman; Soltani, Kiumars; Yin, Junjun; Padmanabhan, Anand; Wang, Shaowen.

In: PloS one, Vol. 12, No. 7, 01.01.2017, p. e0181657.

Research output: Contribution to journalArticle

Soliman, Aiman ; Soltani, Kiumars ; Yin, Junjun ; Padmanabhan, Anand ; Wang, Shaowen. / Social sensing of urban land use based on analysis of Twitter users' mobility patterns. In: PloS one. 2017 ; Vol. 12, No. 7. pp. e0181657.
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