The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data
Open accessAbstract
The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.
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Cited by
Shen, Y., Sun, F., & Che, Y. (2017) · Urban Forestry & Urban Greening · doi:10.1016/j.ufug.2017.06.018 · Cited by 258
Christensen, M. B., Gotfredsen, A., & Nørgaard, K. (2017) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.2885 · Cited by 57
Metadata
- Authors
- Liu, Y., Sui, Z., Kang, C., & Gao, Y.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-01-17
- Volume
- 9
- Issue
- 1
- Pages
- e86026
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2039350330
- Cited by
- 393
- References
- 57
- FWCI
- 85.68
- Type
- journal article
- Language
- en
- Open access
- gold
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