COVIDSensing: Social Sensing strategy for the management of the COVID-19 crisis

Abstract

[EN] The management of the COVID-19 pandemic has been shown to be critical for reducing its dramatic effects. Social sensing can analyse user-contributed data posted daily in social-media services, where participants are seen as Social Sensors. Individually, social sensors may provide noisy information. However, collectively, such opinion holders constitute a large critical mass dispersed everywhere and with an immediate capacity for information transfer. The main goal of this article is to 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 socio-economic and health crisis caused by COVID-19. This tool dynamically identifies socio-economic problems 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 figures together with the social perceptions towards the disease. This article presents the case study of Spain to illustrate the tool.This work is derived from R&D project RTI2018-096384-B-I00, as well as the Ramon y Cajal Grant RYC2018-025580-I, funded by MCIN/AEI/10.13039/501100011033 and ERDF A way of making Europe, by the Spanish Agencia Estatal de Investigación (grant number PID2020- 112827GB-I00/ AEI/10.13039/501100011033), and by the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Proyectos AICO/2020, Spain, under Grant AICO/2020/302.Sepúlveda, A.; Periñán-Pascual, C.; Muñoz, A.; Martínez-España, R.; Hernández-Orallo, E.; Cecilia-Canales, JM. (2021). COVIDSensing: Social Sensing strategy for the management of the COVID-19 crisis. Electronics. 10(24):1-17. https://doi.org/10.3390/electronics10243157S117102