#lockdown: network-enhanced emotional profiling at the times of COVID-19

TL;DR

This paper introduces MERCURIAL, a social media analysis framework that reconstructs emotional profiles during COVID-19 lockdowns, revealing complex feelings like fear, anger, trust, and hope from large-scale Twitter data.

Contribution

The paper presents an innovative network-based framework for analyzing emotional discourse on social media during crises, providing real-time insights into public psychological states.

Findings

Identification of coexisting emotions such as anger, fear, trust, and hope.

Insights into social reactions like solidarity, grief, and calls for violence.

Framework as a tool for policymakers to assess emotional climate rapidly.

Abstract

The COVID-19 pandemic forced countries all over the world to take unprecedented measures like nationwide lockdowns. To adequately understand the emotional and social repercussions, a large-scale reconstruction of how people perceived these unexpected events is necessary but currently missing. We address this gap through social media by introducing MERCURIAL (Multi-layer Co-occurrence Networks for Emotional Profiling), a framework which exploits linguistic networks of words and hashtags to reconstruct social discourse describing real-world events. We use MERCURIAL to analyse 101,767 tweets from Italy, the first country to react to the COVID-19 threat with a nationwide lockdown. The data were collected between 11th and 17th March, immediately after the announcement of the Italian lockdown and the WHO declaring COVID-19 a pandemic. Our analysis provides unique insights into the psychological burden of this crisis, focussing on: (i) the Italian official campaign for self-quarantine (#iorestoacasa}), (ii) national lockdown (#italylockdown), and (iii) social denounce (#sciacalli). Our exploration unveils evidence for the emergence of complex emotional profiles, where anger and fear (towards political debates and socio-economic repercussions) coexisted with trust, solidarity, and hope (related to the institutions and local communities). We discuss our findings in relation to mental well-being issues and coping mechanisms, like instigation to violence, grieving, and solidarity. We argue that our framework represents an innovative thermometer of emotional status, a powerful tool for policy makers to quickly gauge feelings in massive audiences and devise appropriate responses based on cognitive data.