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Introduction: The COVID-19 pandemic has had a number of impacts on people's daily lives around the world. The radical change in people's daily routines has led to an increase in the use and consumption of social media content. The scenario of uncertainty during this period has been favorable to the increase in bouts of anxiety and depression, leading many people to post content about these topics on social media. Objective: Develop a tool that uses natural language processing techniques to analyze Brazilian posts on X, formerly Twitter, during the pandemic. Materials and Methods: We collected and analyzed X posts related to mental health during the COVID-19 pandemic in Brazil. We used sentiment analysis and topic identification methods to evaluate the content of the posts. Results: The results showed that the pandemic has had a negative psychological impact on the lives of Brazilians. The "News" broadcast and the "Symptoms/Disorders" produced caused significant emotional discomfort, with women being the most affected. The analysis revealed an increase in the number of publications related to mental health during the pandemic. Conclusion: This study has identified new information that can help in the construction of public policies to minimize the negative effects of the pandemic on the mental health of the Brazilian population. The analysis of social media posts (X only) can provide valuable insights to better understand people's needs and concerns during public health crises such as the COVID-19 pandemic.
Nogueira et al. (Wed,) studied this question.