#lockdown: network-enhanced emotional profiling at the times of COVID-19
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Abstract (arXiv)
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.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 May 2020.
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Citing papers per year: 2021: 8; 2022: 0; 2023: 0; 2024: 0; 2025: 2.
10 papers.
- 2021Sentiment Analysis and Topic Modeling for COVID-19 Vaccine Discussionscited by 7
- 2021PyPlutchik: visualising and comparing emotion-annotated corporacited by 6
- 2021DASentimental: Detecting depression, anxiety and stress in texts via emotional recall, cognitive networks and machine learningcited by 6
- 2021Cognitive network science for understanding online social cognitions: A brief reviewcited by 5
- 2021A repeated-measures study on emotional responses after a year in the pandemiccited by 3
- 2021Cognitive networks identify the content of English and Italian popular posts about COVID-19 vaccines: Anticipation, logistics, conspiracy and loss of trustcited by 2
- 2021Cognitive network science quantifies feelings expressed in suicide letters and Reddit mental health communitiescited by 2
- 2025ExBigBang: A Dynamic Approach for Explainable Persona Classification through Contextualized Hybrid Transformer Analysiscited by 1
- 2021Network psychometrics and cognitive network science open new ways for detecting, understanding and tackling the complexity of math anxiety: A reviewcited by 0
- 2025The Shifting Landscape of Vaccine Discourse: Insights From a Decade of Pre- to Post-COVID-19 Vaccine Posts on Social Mediacited by 0
- 2025The Shifting Landscape of Vaccine Discourse: Insights From a Decade of Pre- to Post-COVID-19 Vaccine Posts on Social Media20 Nov 2025
- 2025ExBigBang: A Dynamic Approach for Explainable Persona Classification through Contextualized Hybrid Transformer Analysis21 Aug 2025
- 2021Cognitive network science quantifies feelings expressed in suicide letters and Reddit mental health communities28 Oct 2021
- 2021DASentimental: Detecting depression, anxiety and stress in texts via emotional recall, cognitive networks and machine learning26 Oct 2021
- 2021Sentiment Analysis and Topic Modeling for COVID-19 Vaccine Discussions8 Oct 2021
- 2021Network psychometrics and cognitive network science open new ways for detecting, understanding and tackling the complexity of math anxiety: A review31 Aug 2021
- 2021A repeated-measures study on emotional responses after a year in the pandemic7 Jul 2021
- 2021PyPlutchik: visualising and comparing emotion-annotated corpora19 Apr 2021
- 2021Cognitive networks identify the content of English and Italian popular posts about COVID-19 vaccines: Anticipation, logistics, conspiracy and loss of trust29 Mar 2021
- 2021Cognitive network science for understanding online social cognitions: A brief review25 Feb 2021