Prediction of infectious diseases using sentiment analysis on social media data.

ABSTRACT: As the influence and risk of infectious diseases increase, efforts are being made to predict the number of confirmed infectious disease patients, but research involving the qualitative opinions of social media users is scarce. However, social data can change the psychology and behaviors of crowds through information dissemination, which can affect the spread of infectious diseases. Existing studies have used the number of confirmed cases and spatial data to predict the number of confirmed cases of infectious diseases. However, studies using opinions from social data that affect changes in human behavior in relation to the spread of infectious diseases are inadequate. Therefore, herein, we propose a new approach for sentiment analysis of social data by using opinion mining and to predict th

SUBMITTER: Song Y 

PROVIDER: S-EPMC11373815 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature