# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "episomer" in publications use:' type: software license: EUPL-1.0 title: 'episomer: Early Detection of Public Health Threats from Social Media Data' version: 3.0.35 doi: 10.32614/CRAN.package.episomer abstract: It allows you to automatically monitor trends of social media messages by time, place and topic aiming at detecting public health threats early through the detection of signals (i.e., an unusual increase in the number of messages per time, topic and location). 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 on the original package 'epitweetr' is available in the peer-review publication Espinosa et al. (2022) . 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://eu-ecdc.r-universe.dev repository-code: https://github.com/EU-ECDC/episomer commit: 98169519c8166fc5ef8e8604090e78ab36508d9d url: https://github.com/EU-ECDC/episomer date-released: '2026-05-08' contact: - family-names: Espinosa given-names: Laura email: laura.espinosa@ecdc.europa.eu orcid: https://orcid.org/0000-0003-0748-9657