Random Forest location prediction from social networks during disaster events. - TECH-CICO Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Random Forest location prediction from social networks during disaster events.

Résumé

Rapid location and classification of data posted on social networks during time-critical situations such as natural disasters, crowd movement and terrorism is very useful way to gain situational awareness and to plan response efforts. Twitter as successful real time micro-blogging social media, is increasingly used to improve resilience during extreme weather events/emergency management situations, including earthquake. It being used during crises by communicating potential risks and their impacts by informing agencies and officials. The geographical location information of such events are vital to rescue people in danger, or need assistance. However, only few messages contains there native geographical coordinates (GPS). So identifying location is a real challenge with Twitter data during critical situations. Identification of Tweets and their precise location are still inaccurate. In this work, we propose to use semi-supervised technique to utilize unlabeled data, which is often abundant at the onset of a crisis event, along with fewer labeled data. Specifically, we adopt an iterative Random Forest fittingprediction framework to learn the semi-supervised model.
Fichier principal
Vignette du fichier
OUARET_R_etal_RC_SAMSN2019_14.pdf (2.52 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02306003 , version 1 (22-11-2019)

Identifiants

Citer

Rachid Ouaret, B. Birregah, Eddie Soulier, Samuel Auclair, Faïza Boulahya. Random Forest location prediction from social networks during disaster events.. The Sixth IEEE International Conference on Social Networks Analysis, Management and Security, Oct 2019, Granada, Spain. ⟨10.1109/SNAMS.2019.8931863⟩. ⟨hal-02306003⟩
125 Consultations
291 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More