Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/80511
Title: | Towards detecting social events by mining geographical patterns with VGI data | Authors: | Liu, ZW Zhou, XL Shi, WZ Zhang, AS |
Issue Date: | 2018 | Source: | ISPRS international journal of geo-information, Dec. 2018, v. 7, no. 12, 481, p. 1-19 | Abstract: | Detecting events using social media data is important for timely emergency response and urban monitoring. Current studies primarily use semantic-based methods, in which bursts of certain semantic signals are detected to identify emerging events. Nevertheless, our consideration is that a social event will not only affect semantic signals but also cause irregular human mobility patterns. By introducing depictive features, such irregular patterns can be used for event detection. Consequently, in this paper, we develop a novel, comprehensive workflow for event detection by mining the geographical patterns of VGI. This workflow first uses data geographical topic modeling to detect the hashtag communities with VGI semantic data. Both global and local indicators are then constructed by introducing spatial autocorrelation measurements. We then adopt an outlier test and generate indicator maps to spatiotemporally identify the potential social events. This workflow was implemented using a real-world dataset (104,000 geo-tagged photos) and the evaluation was conducted both qualitatively and quantitatively. A set of experiments showed that the discovered semantic communities were internally consistent and externally differentiable, and the plausibility of the detected events was demonstrated by referring to the available ground truth. This study examined the feasibility of detecting events by investigating the geographical patterns of social media data and can be applied to urban knowledge retrieval. | Keywords: | Event detection Volunteered geographic information Geographical pattern mining Feature transformation |
Publisher: | Molecular Diversity Preservation International (MDPI) | Journal: | ISPRS international journal of geo-information | EISSN: | 2220-9964 | DOI: | 10.3390/ijgi7120481 | Rights: | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). The following publication Liu, Z. W., Zhou, X. L., Shi, W. Z., & Zhang, A. S. (2018). Towards detecting social events by mining geographical patterns with vgi data. ISPRS International Journal of Geo-Information, 7(12), 481, 1-19 is available at https://dx.doi.org/10.3390/ijgi7120481 |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Liu_Detecting_Social_VGI.pdf | 2.8 MB | Adobe PDF | View/Open |
Page views
176
Last Week
2
2
Last month
Citations as of Apr 28, 2024
Downloads
88
Citations as of Apr 28, 2024
SCOPUSTM
Citations
5
Citations as of Apr 26, 2024
WEB OF SCIENCETM
Citations
5
Citations as of May 2, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.