About: An Empirical Methodology for Detecting and Prioritizing Needs during Crisis Events

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: An Empirical Methodology for Detecting and Prioritizing Needs during Crisis Events Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	An Empirical Methodology for Detecting and Prioritizing Needs during Crisis Events
Creator	Chin, Chieh-Li Diesner, Jana Dinh, Ly Rezapour, Rezvaneh Sarol, M Yang, Pingjing
topic	covid:7602ca90b8203e17ae00c585f57f04d6dc5e0b26#this
Source	ArXiv
abstract	In times of crisis, identifying the essential needs is a crucial step to providing appropriate resources and services to affected entities. Social media platforms such as Twitter contain vast amount of information about the general public's needs. However, the sparsity of the information as well as the amount of noisy content present a challenge to practitioners to effectively identify shared information on these platforms. In this study, we propose two novel methods for two distinct but related needs detection tasks: the identification of 1) a list of resources needed ranked by priority, and 2) sentences that specify who-needs-what resources. We evaluated our methods on a set of tweets about the COVID-19 crisis. For task 1 (detecting top needs), we compared our results against two given lists of resources and achieved 64% precision. For task 2 (detecting who-needs-what), we compared our results on a set of 1,000 annotated tweets and achieved a 68% F1-score.
has issue date	2020-06-02(xsd:dateTime)
has license	arxiv
sha1sum (hex)	7602ca90b8203e17ae00c585f57f04d6dc5e0b26
resource representing a document's title	An Empirical Methodology for Detecting and Prioritizing Needs during Crisis Events
resource representing a document's body	covid:7602ca90b8203e17ae00c585f57f04d6dc5e0b26#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/7602ca90b8203e17ae00c585f57f04d6dc5e0b26
is schema:about of	named entity 'For' named entity 'However' named entity 'needed' named entity 'study' named entity 'RANKED' named entity 'AFFECTED' named entity 'PRACTITIONERS' named entity 'NEEDS' named entity 'STEP' named entity 'sparsity' named entity 'entities' named entity 'list' named entity 'platforms' named entity 'resources and services' named entity 'services' named entity 'social media' named entity 'Cohen's kappa' named entity 'WHO' named entity 'WHO' named entity 'deep learning' named entity 'U.S.' named entity 'U.S.' named entity 'WHO' named entity '2015 Chennai floods' named entity 'direct object' named entity '2015 Nepal earthquake' named entity 'tweets' named entity 'COVID-19' named entity 'WHO' named entity 'word form' named entity 'regular expressions' named entity 'GitHub' named entity 'personal protective equipment' named entity 'WHO' named entity 'SARS-CoV-2' named entity 'NLTK' named entity 'word embeddings' named entity 'tokenizer' named entity 'training data' named entity 'dependency parse' named entity 'direct object' named entity 'preposition' named entity 'situational awareness' named entity 'crisis informatics' named entity 'WHO' named entity 'parse tree' named entity 'machine learning' named entity 'natural language processing' named entity 'NLTK' named entity 'World Health Organization' named entity 'COVID-19' named entity 'U.S. Department of Health and Human Services' named entity 'COVID19' named entity 'NLTK' named entity 'word embeddings' named entity 'personal protective equipment' named entity 'COVID-19' named entity 'Shang' named entity 'parse tree' named entity 'copular verb' named entity 'tokenizer' named entity 'WHO' named entity 'Twitter' named entity 'social media' named entity 'Twitter' named entity 'natural disaster' named entity 'Crimson Hexagon' named entity 'crisis informatics' named entity 'lexical resource' named entity 'preposition' named entity 'COVID-19' named entity 'Office of Inspector General' named entity 'social media' named entity 'copular verb' named entity 'word form' named entity 'precision, recall' named entity 'WHO' named entity 'NLTK' named entity 'COVID-19 virus outbreak' named entity 'NLTK'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software