@article{Geronikolou_JMIR_2021,
author = {Geronikolou, Styliani and Drosatos, George and Chrousos, George},
title = {Emotional Analysis of Twitter Posts During the First Phase of the COVID-19 Pandemic in Greece: Infoveillance Study},
journal = {JMIR Formative Research},
year = {2021},
month = sept,
volume = {5},
number = {9},
pages = {e27741},
keywords = {emotional analysis; COVID-19; Twitter; Greece; infodemics; emotional contagion; epidemiology; pandemic; mental health},
abstract = {Background: The effectiveness of public health measures depends upon a community's compliance as well as on its positive or negative emotions. Objective: The purpose of this study was to perform an analysis of the expressed emotions in English tweets by Greek Twitter users during the first phase of the COVID-19 pandemic in Greece. Methods: The period of this study was from January 25, 2020 to June 30, 2020. Data collection was performed by using appropriate search words with the filter-streaming application programming interface of Twitter. The emotional analysis of the tweets that satisfied the inclusion criteria was achieved using a deep learning approach that performs better by utilizing recurrent neural networks on sequences of characters. Emotional epidemiology tools such as the 6 basic emotions, that is, joy, sadness, disgust, fear, surprise, and anger based on the Paul Ekman classification were adopted. Results: The most frequent emotion that was detected in the tweets was ``surprise'' at the emerging contagion, while the imposed isolation resulted mostly in ``anger'' (odds ratio 2.108, 95{\%} CI 0.986-4.506). Although the Greeks felt rather safe during the first phase of the COVID-19 pandemic, their positive and negative emotions reflected a masked ``flight or fight'' or ``fear versus anger'' response to the contagion. Conclusions: The findings of our study show that emotional analysis emerges as a valid tool for epidemiology evaluations, design, and public health strategy and surveillance.},
issn = {2561-326X},
doi = {10.2196/27741},
url = {https://formative.jmir.org/2021/9/e27741},
publisher = {JMIR Publications}
}