Volunteered geographic information research in the first decade: a narrative review of selected journal articles in GIScience

Y Yan, CC Feng, W Huang, H Fan… - International Journal of …, 2020 - Taylor & Francis
More than 10 years have passed since the coining of the term volunteered geographic
information (VGI) in 2007. This article presents the results of a review of the literature …

An overview of microblog user geolocation methods

X Luo, Y Qiao, C Li, J Ma, Y Liu - Information processing & management, 2020 - Elsevier
Geographical locations of microblog users are essential for user profiling, event localization
and target advertising, to name a few. Automatic identification of user locations from the …

Using social media to estimate visitor provenance and patterns of recreation in Germany's national parks

M Sinclair, M Mayer, M Woltering… - Journal of Environmental …, 2020 - Elsevier
Social media data are increasingly utilised as a low-cost alternative to visitor surveys in
characterising nature-based recreation. However, the information available on individual …

[HTML][HTML] From Twitter to traffic predictor: Next-day morning traffic prediction using social media data

W Yao, S Qian - Transportation research part C: emerging technologies, 2021 - Elsevier
The effectiveness of traditional traffic prediction methods, such as autoregressive or spatio-
temporal models, is often extremely limited when forecasting traffic dynamics in early …

Beyond spatial proximity—classifying parks and their visitors in London based on spatiotemporal and sentiment analysis of Twitter data

A Kovacs-Györi, A Ristea, R Kolcsar, B Resch… - … International Journal of …, 2018 - mdpi.com
Parks are essential public places and play a central role in urban livability. However,
traditional methods of investigating their attractiveness, such as questionnaires and in situ …

Identifying home locations in human mobility data: an open-source R package for comparison and reproducibility

Q Chen, A Poorthuis - International Journal of Geographical …, 2021 - Taylor & Francis
Identifying meaningful locations, such as home or work, from human mobility data has
become an increasingly common prerequisite for geographic research. Although location …

Exploring the uncertainty of activity zone detection using digital footprints with multi-scaled DBSCAN

X Liu, Q Huang, S Gao - Uncertainty and Context in GIScience …, 2021 - taylorfrancis.com
The density-based spatial clustering of applications with noise (DBSCAN) method is often
used to identify individual activity clusters (ie, zones) using digital footprints captured from …

Exploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique

H Li, B Herfort, W Huang, M Zia, A Zipf - ISPRS Journal of Photogrammetry …, 2020 - Elsevier
Accurate and detailed geographical information digitizing human activity patterns plays an
essential role in response to natural disasters. Volunteered geographical information, in …

Private, public, personal: Shifting patterns in geospatial data sources in geographic research

G Appiah, M Kaufman, B Cooney… - Annals of the American …, 2024 - Taylor & Francis
Geospatial data sources include data collected by the public sector (ie, government), private
sector (ie, industry), or through field work. Of these categories, the private sector, especially …

Please forget where I was last summer: The privacy risks of public location (meta) data

K Drakonakis, P Ilia, S Ioannidis, J Polakis - arXiv preprint arXiv …, 2019 - arxiv.org
The exposure of location data constitutes a significant privacy risk to users as it can lead to
de-anonymization, the inference of sensitive information, and even physical threats. In this …