Evidence map›Paper›PMID 36570490›Full record

ArticleInternational journal of applied earth observation and geoinformation : ITC journal2023

A global portrait of expressed mental health signals towards COVID-19 in social media space.

Siqin Wang, Xiao Huang, Tao Hu, Bing She, Mengxi Zhang, Ruomei Wang, Oliver Gruebner, Muhammad Imran, Jonathan Corcoran, Yan Liu and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of applied earth observation and geoinformation : ITC journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
5.1field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 14 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 7 institutions in 5 countries.

Siqin WangSchool of Earth and Environmental Sciences, University of Queensland, Brisbane, Queensland, Australia.
Xiao HuangDepartment of Geosciences, University of Arkansas, AR, USA.
Tao HuDepartment of Geography, Oklahoma State University, OK, USA.
Bing SheInstitute for Social Research, University of Michigan, MI, USA.
Mengxi ZhangDepartment of Nutrition and Health Science, Ball State University, IN, USA.
Ruomei WangSchool of Earth and Environmental Sciences, University of Queensland, Brisbane, Queensland, Australia.
Oliver GruebnerDepartment of Geography, University of Zurich, Switzerland.
Muhammad ImranQatar Computing Research Institute, Hamad Bin Khalifa University, Qatar.
Jonathan CorcoranSchool of Earth and Environmental Sciences, University of Queensland, Brisbane, Queensland, Australia.
Yan LiuSchool of Earth and Environmental Sciences, University of Queensland, Brisbane, Queensland, Australia.
Shuming BaoChina Data Institute and Future Data Lab, MI, USA.
Harvard University · USUniversity of Queensland · AUChina Datang Corporation (China) · CNHamad bin Khalifa University · QAOklahoma State University Oklahoma City · USUniversity of Michigan–Ann Arbor · USUniversity of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Globally, the COVID-19 pandemic has induced a mental health crisis. Social media data offer a unique opportunity to track the mental health signals of a given population and quantify their negativity towards COVID-19. To date, however, we know little about how negative sentiments differ across countries and how these relate to the shifting policy landscape experienced through the pandemic. Using 2.1 billion individual-level geotagged tweets posted between 1 February 2020 and 31 March 2021, we track, monitor and map the shifts in negativity across 217 countries and unpack its relationship with COVID-19 policies. Findings reveal that there are important geographic, demographic, and socioeconomic disparities of negativity across continents, different levels of a nation's income, population density, and the level of COVID-19 infection. Countries with more stringent policies were associated with lower levels of negativity, a relationship that weakened in later phases of the pandemic. This study provides the first global and multilingual evaluation of the public's real-time mental health signals to COVID-19 at a large spatial and temporal scale. We offer an empirical framework to monitor mental health signals globally, helping international authorizations, including the United Nations and World Health Organization, to design smart country-specific mental health initiatives in response to the ongoing pandemic and future public emergencies.

Indexed as

COVID-19Multilingual tweetsNegative sentimentsPandemicPolicy implementationSentiment analysisSocial media

Identifiers

PMID36570490
PMCPMC9759272
OpenAlexW4311796245

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.