2018, Volume 12, Issue 5
Frontiers of Environmental Science & Engineering >> 2018, Volume 12, Issue 5 doi: 10.1007/s11783-018-1068-1
Social media and mobility landscape: Uncovering spatial patterns of urban human mobility with multi source data
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Abstract
Check-in and survey data are explored to identify personal activity-specific places. Ways for detecting and moderating sample bias of Weibo check-in data is proposed. A graphic representation of urban activity intensity in Beijing, China is presented. The potential application of Weibo check-in data for urban analysis is introduced.
Keywords
Social media ; Human mobility ; Population bias ; Sample reconstruction ; Data integration
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