RT journal article
T1 COVIDSensing: Social Sensing Strategy for the Management of the COVID-19 Crisis
A1 Sepúlveda, Alicia
A1 Periñán-Pascual, Carlos
A1 Muñoz Ortega, Andrés
A1 Martínez-España, Raquel
A1 Hernández-Orallo, Enrique
A1 Cecilia, José M.
A2 Ingeniería Informática
K1 social sensing
K1 COVID-19
K1 Natural Language Processing
K1 Machine Learning
K1 data analysis
AB The management of the COVID-19 pandemic has been shown to be critical for reducingits dramatic effects. Social sensing can analyse user-contributed data posted daily in social-mediaservices, where participants are seen as Social Sensors. Individually, social sensors may provide noisyinformation. However, collectively, such opinion holders constitute a large critical mass dispersedeverywhere and with an immediate capacity for information transfer. The main goal of this article isto present a novel methodological tool based on social sensing, called COVIDSensing. In particular,this application serves to provide actionable information in real time for the management of the socioeconomicand health crisis caused by COVID-19. This tool dynamically identifies socio-economicproblems of general interest through the analysis of people’s opinions on social networks. Moreover,it tracks and predicts the evolution of the COVID-19 pandemic based on epidemiological figurestogether with the social perceptions towards the disease. This article presents the case study of Spainto illustrate the tool.
PB MDPI
YR 2021
FD 2021-12
LK http://hdl.handle.net/10498/26435
UL http://hdl.handle.net/10498/26435
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 12-nov-2026