# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "epitweetr" in publications use:'
type: software
license: EUPL-1.0
title: 'epitweetr: Early Detection of Public Health Threats from ''Twitter'' Data'
version: 2.2.16
doi: 10.32614/CRAN.package.epitweetr
abstract: It allows you to automatically monitor trends of tweets by time, place and
  topic aiming at detecting public health threats early through the detection of signals
  (e.g. an unusual increase in the number of tweets). It was designed to focus on
  infectious diseases, and it can be extended to all hazards or other fields of study
  by modifying the topics and keywords. More information is available in the 'epitweetr'
  peer-review publication (doi:10.2807/1560-7917.ES.2022.27.39.2200177).
authors:
- family-names: Espinosa
  given-names: Laura
  email: laura.espinosa@ecdc.europa.eu
  orcid: https://orcid.org/0000-0003-0748-9657
- family-names: Orchard
  given-names: Francisco
  email: f.orchard@epiconcept.fr
  orcid: https://orcid.org/0000-0001-5793-3301
repository: https://epiverse-connect.r-universe.dev
repository-code: https://github.com/EU-ECDC/epitweetr
commit: cbfa8fa1cd3e3d63e0577ec22fc432c108fd5e34
url: https://github.com/EU-ECDC/epitweetr
contact:
- family-names: Espinosa
  given-names: Laura
  email: laura.espinosa@ecdc.europa.eu
  orcid: https://orcid.org/0000-0003-0748-9657