"OMG, from here, I can see the flames!": a use case of mining location based social networks to acquire spatio-temporal data on forest fires
Abstract
The emergence of innovative web applications, often labelled as Web 2.0, has permitted an unprecedented increase of content created by non-specialist users. In particular, Location-based Social Networks (LBSN) are designed as platforms allowing the creation, storage and retrieval of vast amounts of georeferenced and user-generated contents. LBSN can thus be seen by Geographic Information specialists as a timely and cost-effective source of spatio-temporal information for many fields of application, provided that they can set up workflows to retrieve, validate and organise such information. This paper aims to improve the understanding on how LBSN can be used as a reliable source of spatio-temporal information, by analysing the temporal, spatial and social dynamics of Twitter activity during a major forest fire event in the South of France in July 2009.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The Guardian list classified the top image URLs shared during Hurricane Sandy as fake or real image URLs.
“The list provided by Gaurdian, classified the top image URLs shared during the hurricane as fake or real image URLs, which we used to form our dataset.”
From Faking Sandy: Characterizing and identifying fake images on Twitter during Hurricane Sandy (2013) · cites this paper as [9]
Cited by
Sorted by citations
Processing Social Media Messages in Mass Emergency: A Survey
Imran, M., Castillo, C., Diaz, F., & Vieweg, S. (2015) · ACM Computing Surveys · doi:10.1145/2771588 · Cited by 804 · see citing works
Gupta, A., Lamba, H., Kumaraguru, P., & Joshi, A. (2013) · Proceedings of the 22nd International Conference on World Wide Web Companion · doi:10.1145/2487788.2488033 · Cited by 573 · see citing works
Martínez-Rojas, M., Pardo-Ferreira, M. D. C., & Rubio-Romero, J. C. (2018) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2018.07.008 · Cited by 213 · see citing works
Automated Emerging Cyber Threat Identification and Profiling Based on Natural Language Processing
Marinho, R., & Holanda, R. (2023) · IEEE Access · doi:10.1109/access.2023.3260020 · Cited by 50 · see citing works
- Authors
- De Longueville, B., Smith, R. S., & Luraschi, G.
- Affiliations
- Institute for Environment & Sustainability, Ispra, Italy
- ORCID
- Smith, Robin S.
- Venue
- Proceedings of the 2009 International Workshop on Location Based Social Networks
- Publisher
- ACM
- Published
- 2009-11-03
- Pages
- 73-80
- OpenAlex
- W2070722606
- Cited by
- 307
- References
- 0
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 2 · 2023: 9 · 2022: 5 · 2021: 17 · 2020: 16 · 2019: 15 · 2018: 27 · 2017: 27 · 2016: 28 · 2015: 35 · 2014: 41 · 2013: 29 · 2012: 25
- FWCI
- 53.77
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Joint Research Centre (European Commission) (submittedVersion)
- Topics
- Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Social Sciences › Communication › Public Relations and Crisis Communication
- Keywords
- location-based social networks, Twitter, forest fires, spatio-temporal information, user-generated content, georeferenced records, social dynamics, temporal dynamics, spatial dynamics, wildfire monitoring
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
