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globalchange > 过去全球变化的重建

DOI:	10.1371/journal.pone.0086026
论文题名:	Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data
作者:	Yu Liu; Zhengwei Sui; Chaogui Kang; Yong Gao
刊名:	PLOS ONE
ISSN:	1932-6203
出版年:	2014
发表日期:	2014-1-17
卷:	9, 期:1
语种:	英语
英文关键词:	Human mobility ; Algorithms ; Geoinformatics ; Social media ; Statistical distributions ; China ; Geographic distribution ; Specific gravity
英文摘要:	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.
URL:	http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0086026&type=printable
Citation statistics:
资源类型:	期刊论文
标识符:	http://119.78.100.158/handle/2HF3EXSE/19713
Appears in Collections:	过去全球变化的重建影响、适应和脆弱性科学计划与规划气候变化与战略全球变化的国际研究计划气候减缓与适应气候变化事实与影响

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File Name/ File Size	Content Type	Version	Access	License
journal.pone.0086026.PDF（1212KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	View Download

作者单位:

Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing, China;Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing, China;Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing, China;Institute of Remote Sensing and Geographical Information Systems, Peking University, Beijing, China

Recommended Citation:

Yu Liu,Zhengwei Sui,Chaogui Kang,et al. Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data[J]. PLOS ONE,2014-01-01,9(1)

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