Concerns Discussed on Chinese and French Social Media During the COVID-19 Lockdown: Comparative Infodemiology Study Based on Topic Modeling.

COVID-19 China France comparative analysis content analysis impact lockdown population social media topic model

Journal

JMIR formative research
ISSN: 2561-326X
Titre abrégé: JMIR Form Res
Pays: Canada
ID NLM: 101726394

Informations de publication

Date de publication:
05 Apr 2021
Historique:
received: 17 08 2020
accepted: 15 03 2021
revised: 18 09 2020
pubmed: 23 3 2021
medline: 23 3 2021
entrez: 22 3 2021
Statut: epublish

Résumé

During the COVID-19 pandemic, numerous countries, including China and France, have implemented lockdown measures that have been effective in controlling the epidemic. However, little is known about the impact of these measures on the population as expressed on social media from different cultural contexts. This study aims to assess and compare the evolution of the topics discussed on Chinese and French social media during the COVID-19 lockdown. We extracted posts containing COVID-19-related or lockdown-related keywords in the most commonly used microblogging social media platforms (ie, Weibo in China and Twitter in France) from 1 week before lockdown to the lifting of the lockdown. A topic model was applied independently for three periods (prelockdown, early lockdown, and mid to late lockdown) to assess the evolution of the topics discussed on Chinese and French social media. A total of 6395; 23,422; and 141,643 Chinese Weibo messages, and 34,327; 119,919; and 282,965 French tweets were extracted in the prelockdown, early lockdown, and mid to late lockdown periods, respectively, in China and France. Four categories of topics were discussed in a continuously evolving way in all three periods: epidemic news and everyday life, scientific information, public measures, and solidarity and encouragement. The most represented category over all periods in both countries was epidemic news and everyday life. Scientific information was far more discussed on Weibo than in French tweets. Misinformation circulated through social media in both countries; however, it was more concerned with the virus and epidemic in China, whereas it was more concerned with the lockdown measures in France. Regarding public measures, more criticisms were identified in French tweets than on Weibo. Advantages and data privacy concerns regarding tracing apps were also addressed in French tweets. All these differences were explained by the different uses of social media, the different timelines of the epidemic, and the different cultural contexts in these two countries. This study is the first to compare the social media content in eastern and western countries during the unprecedented COVID-19 lockdown. Using general COVID-19-related social media data, our results describe common and different public reactions, behaviors, and concerns in China and France, even covering the topics identified in prior studies focusing on specific interests. We believe our study can help characterize country-specific public needs and appropriately address them during an outbreak.

Sections du résumé

BACKGROUND BACKGROUND
During the COVID-19 pandemic, numerous countries, including China and France, have implemented lockdown measures that have been effective in controlling the epidemic. However, little is known about the impact of these measures on the population as expressed on social media from different cultural contexts.
OBJECTIVE OBJECTIVE
This study aims to assess and compare the evolution of the topics discussed on Chinese and French social media during the COVID-19 lockdown.
METHODS METHODS
We extracted posts containing COVID-19-related or lockdown-related keywords in the most commonly used microblogging social media platforms (ie, Weibo in China and Twitter in France) from 1 week before lockdown to the lifting of the lockdown. A topic model was applied independently for three periods (prelockdown, early lockdown, and mid to late lockdown) to assess the evolution of the topics discussed on Chinese and French social media.
RESULTS RESULTS
A total of 6395; 23,422; and 141,643 Chinese Weibo messages, and 34,327; 119,919; and 282,965 French tweets were extracted in the prelockdown, early lockdown, and mid to late lockdown periods, respectively, in China and France. Four categories of topics were discussed in a continuously evolving way in all three periods: epidemic news and everyday life, scientific information, public measures, and solidarity and encouragement. The most represented category over all periods in both countries was epidemic news and everyday life. Scientific information was far more discussed on Weibo than in French tweets. Misinformation circulated through social media in both countries; however, it was more concerned with the virus and epidemic in China, whereas it was more concerned with the lockdown measures in France. Regarding public measures, more criticisms were identified in French tweets than on Weibo. Advantages and data privacy concerns regarding tracing apps were also addressed in French tweets. All these differences were explained by the different uses of social media, the different timelines of the epidemic, and the different cultural contexts in these two countries.
CONCLUSIONS CONCLUSIONS
This study is the first to compare the social media content in eastern and western countries during the unprecedented COVID-19 lockdown. Using general COVID-19-related social media data, our results describe common and different public reactions, behaviors, and concerns in China and France, even covering the topics identified in prior studies focusing on specific interests. We believe our study can help characterize country-specific public needs and appropriately address them during an outbreak.

Identifiants

pubmed: 33750736
pii: v5i4e23593
doi: 10.2196/23593
pmc: PMC8023382
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e23593

Informations de copyright

©Stéphane Schück, Pierre Foulquié, Adel Mebarki, Carole Faviez, Mickaïl Khadhar, Nathalie Texier, Sandrine Katsahian, Anita Burgun, Xiaoyi Chen. Originally published in JMIR Formative Research (http://formative.jmir.org), 05.04.2021.

Auteurs

Carole Faviez (C)

Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Paris, France.

Sandrine Katsahian (S)

Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Paris, France.
Unité d'Épidémiologie et de Recherche Clinique, Hôpital européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.

Anita Burgun (A)

Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Paris, France.
Département d'informatique médicale, Hôpital européen Georges Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France.
Département d'informatique médicale, Hôpital Necker-Enfants Malades, Assistance Publique - Hôpitaux de Paris, Paris, France.
Paris Artificial Intelligence Research Institute, Paris, France.

Xiaoyi Chen (X)

Centre de Recherche des Cordeliers, INSERM, Sorbonne Université, Université de Paris, Paris, France.

Classifications MeSH