Sentiment analysis of epidemiological surveillance reports on COVID-19 in Greece using machine learning models.

ABSTRACT: The present research deals with sentiment analysis performed with Microsoft Azure Machine Learning Studio to classify Facebook posts on the Greek National Public Health Organization (EODY) from November 2021 to January 2022 during the pandemic. Positive, negative and neutral sentiments were included after processing 300 reviews. This approach involved analyzing the words appearing in the comments and exploring the sentiments related to daily surveillance reports of COVID-19 published on the EODY Facebook page. Moreover, machine learning algorithms were implemented to predict the classification of sentiments. This research assesses the efficiency of a few popular machine learning models, which is one of the initial efforts in Greece in this domain. People have negative sentiments toward COV

SUBMITTER: Stefanis C 

PROVIDER: S-EPMC10392838 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature