Bilingual emotion analysis in social media throughout the COVID19 pandemic in Portugal

Alina Trifan, Sérgio Matos, Pedro Morgado, José Luís Oliveira

Keywords: emotion anaysis, social media, mental health, NLP

TL;DR: We collected, curated and analyzed covid-related tweets of users in Portugal posted during four and a half months (January to May 2020) in order to understand the evolution of the six basic emotions reflected in these tweets.

Abstract: This paper presents preliminary work on the topic of emotion analysis on Twitter, in the context of the coronavirus pandemic in Portugal. We collected, curated and analyzed covid-related tweets of users in Portugal posted during four and a half months (January to May 2020) in order to understand the evolution of the six basic emotions reflected in these tweets. We analyzed tweets written in both English and Portuguese. In this first step of our work we correlate this information with key events of the evolution of the pandemic in Portugal during March, which was the most critical period in Portugal. Our findings show that the sentiment analysis of covid-related twees is consistent with our hypothesis that negative emotions would intensify as the pandemic progressed. The preliminary results obtained stand as proof of concept that the analysis of real-time tweets or other social media messages through sentiment analysis can be an important tool for behavioural and well-being tracking.