Delineating and modeling activity space using geotagged social media data

ABSTRACT

It has become increasingly important in spatial equity studies to understand activity spaces – where people conduct regular out-of-home activities. Big data can advance the identification of activity spaces and the understanding of spatial equity. Using the Los Angeles metropolitan area for the case study, this paper employs geotagged Twitter data to delineate activity spaces with two spatial measures: first, the average distance between users’ home location and activity locations; and second, the area covered between home and activity locations. The paper also finds significant relationship between the spatial measures of activity spaces and neighborhood spatial and socioeconomic characteristics. This research enriches the literature that aims to address spatial equity in activity spaces and demonstrates the applicability of big data in urban socio-spatial research.

KEYWORDS:

• Twitter
• equity
• deviational ellipse
• neighborhood
• Los Angeles
• activity space

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This material is partially based upon work supported by the National Science Foundation under Grant Nos. [1416509 and 1739491] and University of South Carolina Grant No.[13540-18-48955]. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation and University of South Carolina.