Social media can be an invaluable help in a mass emergency, but the information handling can be challenging. One major concern is identifying posts related to the area, or pinning them on a map. This exploratory study analyzes the spatial data coming with tweets during two natural disasters, an earthquake and a hurricane. Geo-tagged tweets confirm to be a small fraction of all tweets and disasters within a limited region appear to be a niche topic in the whole stream. The results can help researchers and practitioners in the design of tools to identify these messages.

Analyzing spatial data from twitter during a disaster / Venturini, Luca; DI CORSO, Evelina. - ELETTRONICO. - (2017), pp. 3779-3783. ((Intervento presentato al convegno Big Data (Big Data), 2017 IEEE International Conference on tenutosi a Boston (USA) nel 11-14 Dec. 2017 [10.1109/BigData.2017.8258378].

Analyzing spatial data from twitter during a disaster

Venturini, Luca;DI CORSO, EVELINA
2017

Abstract

Social media can be an invaluable help in a mass emergency, but the information handling can be challenging. One major concern is identifying posts related to the area, or pinning them on a map. This exploratory study analyzes the spatial data coming with tweets during two natural disasters, an earthquake and a hurricane. Geo-tagged tweets confirm to be a small fraction of all tweets and disasters within a limited region appear to be a niche topic in the whole stream. The results can help researchers and practitioners in the design of tools to identify these messages.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2697727
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