Evidence map›Paper›PMID 33078073›Full record

ArticleHealth information science and systems2020

How can social media analytics assist authorities in pandemic-related policy decisions? Insights from Australian states and territories.

Tan Yigitcanlar, Nayomi Kankanamge, Alexander Preston, Palvinderjit Singh Gill, Maqsood Rezayee, Mahsan Ostadnia, Bo Xia, Giuseppe Ioppolo

Open access · hybridAbstract read
In one paragraph

Article in Health information science and systems, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
12.9field-weighted citation impact, top 1% 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 55 citations in OpenAlex.

  1. When Infodemic Meets Epidemic: Systematic Literature Review.JMIR public health and surveillance · 2025
    Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. The Role of Social Media in Building Pandemic Resilience in an Urban Community: A Qualitative Case Study.International journal of environmental research and public health · 2023
    Article
  6. Impacts of Covid-19 interventions on air quality: evidence from Brazilian metropolitan regions.International journal of environmental science and technology : IJEST · 2023
    Article
  7. Article
  8. Article
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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

8 authors at 4 institutions in 4 countries.

Tan YigitcanlarSchool of Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000 Australia.ORCID 0000-0001-7262-7118
Nayomi KankanamgeSchool of Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000 Australia.ORCID 0000-0002-4529-7042
Alexander PrestonSchool of Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000 Australia.
Palvinderjit Singh GillSchool of Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000 Australia.
Maqsood RezayeeDepartment of Architecture, Nangarhar University, Kabul-Jalal Abad Highway, Jalalabad, Nangarhar 2601 Afghanistan.
Mahsan OstadniaDepartment of Urban Planning, Islamic Azad University, Shariati Street, 19395 Tehran, Iran.
Bo XiaSchool of Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000 Australia.ORCID 0000-0001-7694-4743
Giuseppe IoppoloDepartment of Economics, University of Messina, Piazza Pugliatti, 1, 98122 Messina, Italy.ORCID 0000-0003-0262-8435
Queensland University of Technology · AUIslamic Azad University, Tehran · IRNangarhar University · AFUniversity of Messina · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesDue to COVID-19, various countries introduced lockdowns and limited citizen movements. These restrictions triggered an increased use of digital technologies and platforms by the public. This provides an opportunity for the authorities to capture public perceptions on COVID-19 from social media channels to make informed decisions. The use of social media analytics during pandemics for decision-making, however, is an understudied area of research. Thus, this study aims to generate insights into how social media analytics can assist authorities in pandemic-related policy decisions.

methodsThis study involved a social media analysis approach-i.e., systematic geo-Twitter analysis-that contains descriptive, content, sentiment, and spatial analyses. Australian states and territories are selected as the case study context for the empirical investigation. This study collected 96,666 geotagged tweets (originated from Australia between 1 January and 4 May 2020), and analysed 35,969 of them after data cleaning.

resultsThe findings disclose that: (a) Social media analytics is an efficient approach to capture the attitudes and perceptions of the public during a pandemic; (b) Crowdsourced social media data can guide interventions and decisions of the authorities during a pandemic, and; (c) Effective use of government social media channels can help the public to follow the introduced measures/restrictions.

conclusionThe findings are invaluable for authorities to understand community perceptions and identify communities in needs and demands in a pandemic situation, where authorities are not in a position to conduct direct and lengthily public consultations.

Indexed as

AustraliaCOVID-19Crowdsources dataPandemic-related policySocial media analyticsUrban informatics

Identifiers

PMID33078073
PMCPMC7561284
OpenAlexW3044690939

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.