2020
DOI: 10.1080/13658816.2020.1847288
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Analysis of the performance and robustness of methods to detect base locations of individuals with geo-tagged social media data

Abstract: Various methods have been proposed to detect the base locations of individuals, with their geo-tagged social media data. However, a common challenge relating to base-location detection methods (BDMs) is that, the rare availability of ground-truth data impedes the method assessment of accuracy and robustness, thus undermining research validity and reliability. To address this challenge, we collect users' information from unstructured online content, and evaluate both the performance and robustness of BDMs. The … Show more

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Cited by 18 publications
(7 citation statements)
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“…Coupling with the spatial autocorrelation of hazards, human mobility law related to decay effect (i.e., “individuals are more likely to visit nearby regions”) is possibly another cause for accentuated traveling-induced hazard exposures. , The human mobility patterns are greatly influenced by the urban environment and transportation. , Given that people tend to frequent places that are closer to their residence, their mobility patterns essentially increase their dwell time in high-hazard environments if they live in high-risk areas. If their home and nearby regions share similar hazard characteristics due to spatial autocorrelation, their likelihood of exposure increases with each trip they make within this radius.…”
Section: Discussionmentioning
confidence: 99%
“…Coupling with the spatial autocorrelation of hazards, human mobility law related to decay effect (i.e., “individuals are more likely to visit nearby regions”) is possibly another cause for accentuated traveling-induced hazard exposures. , The human mobility patterns are greatly influenced by the urban environment and transportation. , Given that people tend to frequent places that are closer to their residence, their mobility patterns essentially increase their dwell time in high-hazard environments if they live in high-risk areas. If their home and nearby regions share similar hazard characteristics due to spatial autocorrelation, their likelihood of exposure increases with each trip they make within this radius.…”
Section: Discussionmentioning
confidence: 99%
“…GPS data can provide an individual's location sequence information over a given time span, which contributes to almost real-time snapshots of human mobility, helping to overcome the limitations of self-reported surveys ( 30 , 31 ). Using a combination of human mobility indicators generated from integrated mobile phone GPS data and urban data (e.g., points of interest, land use), researchers can investigate the effects of restrictions on dynamic human activity behaviors (e.g., commuting, place visits, travel mode) with fine granularity ( 32 – 34 ). Moreover, location-based mobile phone GPS data can be easily merged with census socio-demographic data by matching the geospatial information, which helps to examine the socio-economic determinants in human mobility variations.…”
Section: Reviews Of Related Workmentioning
confidence: 99%
“…With the development of Internet technology, social media has become a popular form of media, and it provides new channels for information sources as well as rapid communication [ 9 ]. Social media platforms contain diverse types of information and provides researchers in various fields with diverse research ideas, such as using geotagging data from social media platforms to evaluate the performance and robustness of methods to detect individuals’ basic locations [ 10 ]; using location-based social network data to provide innovative ideas to classify cultural tourist attractions and understand the preferences and needs of tourist groups [ 11 ]; and using social media data to analyze the perceptual characteristics of investor sentiments and stock correlations and construct nonlinear models to complete stock price predictions, which have been conducted by some researchers [ 12 ] in the financial field.…”
Section: Introductionmentioning
confidence: 99%