Tracking the COVID-19 outbreak in India through Twitter: Opportunities for social media based global pandemic surveillance.
AMIA Annu Symp Proc
; 2022: 313-322, 2022.
Artículo
en Inglés
| MEDLINE | ID: covidwho-20238373
ABSTRACT
We investigated the utility of Twitter for conducting multi-faceted geolocation-centric pandemic surveillance, using India as an example. We collected over 4 million COVID19-related tweets related to the Indian outbreak between January and July 2021. We geolocated the tweets, applied natural language processing to characterize the tweets (eg., identifying symptoms and emotions), and compared tweet volumes with the numbers of confirmed COVID-19 cases. Tweet numbers closely mirrored the outbreak, with the 7-day average strongly correlated with confirmed COVID-19 cases nationally (Spearman r=0.944; p=0.001), and also at the state level (Spearman r=0.84, p=0.0003). Fatigue, Dyspnea and Cough were the top symptoms detected, while there was a significant increase in the proportion of tweets expressing negative emotions (eg., fear and sadness). The surge in COVID-19 tweets was followed by increased number of posts expressing concern about black fungus and oxygen supply. Our study illustrates the potential of social media for multi-faceted pandemic surveillance.
Texto completo:
Disponible
Colección:
Bases de datos internacionales
Base de datos:
MEDLINE
Asunto principal:
Medios de Comunicación Sociales
/
COVID-19
Tipo de estudio:
Estudio observacional
Límite:
Humanos
Idioma:
Inglés
Revista:
AMIA Annu Symp Proc
Asunto de la revista:
Informática Médica
Año:
2022
Tipo del documento:
Artículo
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