
GPS location data can reveal information about individuals’ everyday lives, something that conventional data sources like census data cannot do. However, one major limitation of GPS location data is that almost always the location will be recorded with a level of error, known as positional uncertainty. This paper works around the above limitation by aggregating the data at the MSOA level and performing origin-destination analysis. Origin-destination matrices are created to investigate interaction flows and reveal insights on MSOA level connections. We discuss how the analysis can benefit policymakers and public transport providers.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
