Multimodal Damage Identification for Humanitarian Computing
Donated on 6/1/2018
5879 captioned images (image and text) from social media related to damage during natural disasters/wars, and belong to 6 classes: Fires, Floods, Natural landscape, Infrastructural, Human, Non-damage.
Dataset Characteristics
Multivariate, Text
Subject Area
Social
Associated Tasks
Classification
Attribute Type
Integer
# Instances
5879
# Attributes
-
Information
Additional Information
Samples were retrieved from social media posts including Instagram and Twitter.
Attribute Information
Additional Information
640x640 RGB images and raw text
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Citation
Mouzannar,Hussein, Rizk,Yara, and Awad,Mariette. (2018). Multimodal Damage Identification for Humanitarian Computing. UCI Machine Learning Repository. https://doi.org/10.24432/C52P6P.
BibTeX
@misc{misc_multimodal_damage_identification_for_humanitarian_computing_456,
author = {Mouzannar,Hussein, Rizk,Yara, and Awad,Mariette},
title = {{Multimodal Damage Identification for Humanitarian Computing}},
year = {2018},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C52P6P}
}Creators
Hussein Mouzannar
Yara Rizk
Mariette Awad
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.