Text Mining Techniques to Detect Psychological Problems Caused by the COVID-19 Pandemic
摘要
Mental health in a pandemic is an aspect that has not received the necessary attention. If the mental state of a population is evaluated, the development of abnormal behaviors can be prevented, as well as the development of psychological disorders. This article develops an analytical model that allows to detect the main psychological problems that can affect a group of people as a result of a pandemic. The data was collected from tweets that refer to the pandemic caused by Covid-19. The technique used for data analysis was part of speech based on the dictionary of feelings and emotions Emolex. The results show the most common psychological problems found in a country or region on the American continent in Spanish-speaking populations. This study may be also useful to be better prepared for possible new pandemics by creating special public health policies.