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

• Auteurs principaux: Christos Stefanis (Auteur), Elpida Giorgi (Auteur), Konstantinos Kalentzis (Auteur), Athanasios Tselemponis (Auteur), Evangelia Nena (Auteur), Christina Tsigalou (Auteur), Christos Kontogiorgis (Auteur), Yiannis Kourkoutas (Auteur), Ekaterini Chatzak (Auteur), Ioannis Dokas (Auteur), Theodoros Constantinidis (Auteur), Eugenia Bezirtzoglou (Auteur)
• Format: Livre
• Publié: Frontiers Media S.A., 2023-07-01T00:00:00Z.
• Sujets: article
• Accès en ligne: Connect to this object online.

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...