Evidence map›Paper›PMID 34519659›Full record

ArticleJournal of medical Internet research2021

Public Sentiment and Discourse on Domestic Violence During the COVID-19 Pandemic in Australia: Analysis of Social Media Posts.

Kim Usher, Joanne Durkin, Sam Martin, Samantha Vanderslott, Cecilia Vindrola-Padros, Luke Usher, Debra Jackson

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.3field-weighted citation impact, top 10% 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

7 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
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  3. Article
  4. Article
  5. Public Health Directives in a Pandemic: Paradoxical Messages for Domestic Abuse Victims in Four Countries.International journal of environmental research and public health · 2022
    Review
  6. Article
  7. 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

7 authors at 5 institutions in 2 countries.

Kim UsherUniversity of New England, Armidale, Australia.ORCID 0000-0002-9686-5003
Joanne DurkinUniversity of New England, Armidale, Australia.ORCID 0000-0001-9948-4794
Sam MartinOxford Vaccine Group, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4466-8374
Samantha VanderslottOxford Vaccine Group, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-8685-7758
Cecilia Vindrola-PadrosUniversity College London, London, United Kingdom.ORCID 0000-0001-7859-1646
Luke UsherGriffith University, Goldcoast, Australia.ORCID 0000-0001-8705-4148
Debra JacksonUniversity of Sydney, Sydney, Australia.ORCID 0000-0001-5252-5325
University of New England · AUUniversity of Oxford · GBGriffith University · AUThe University of Sydney · AUUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeasuring public response during COVID-19 is an important way of ensuring the suitability and effectiveness of epidemic response efforts. An analysis of social media provides an approximation of public sentiment during an emergency like the current pandemic. The measures introduced across the globe to help curtail the spread of the coronavirus have led to the development of a situation labeled as a "perfect storm," triggering a wave of domestic violence. As people use social media to communicate their experiences, analyzing public discourse and sentiment on social platforms offers a way to understand concerns and issues related to domestic violence during the COVID-19 pandemic.

objectiveThis study was based on an analysis of public discourse and sentiment related to domestic violence during the stay-at-home periods of the COVID-19 pandemic in Australia in 2020. It aimed to understand the more personal self-reported experiences, emotions, and reactions toward domestic violence that were not always classified or collected by official public bodies during the pandemic.

methodsWe searched social media and news posts in Australia using key terms related to domestic violence and COVID-19 during 2020 via digital analytics tools to determine sentiments related to domestic violence during this period.

resultsThe study showed that the use of sentiment and discourse analysis to assess social media data is useful in measuring the public expression of feelings and sharing of resources in relation to the otherwise personal experience of domestic violence. There were a total of 63,800 posts across social media and news media. Within these posts, our analysis found that domestic violence was mentioned an average of 179 times a day. There were 30,100 tweets, 31,700 news reports, 1500 blog posts, 548 forum posts, and 7 comments (posted on news and blog websites). Negative or neutral sentiment centered on the sharp rise in domestic violence during different lockdown periods of the 2020 pandemic, and neutral and positive sentiments centered on praise for efforts that raised awareness of domestic violence as well as the positive actions of domestic violence charities and support groups in their campaigns. There were calls for a positive and proactive handling (rather than a mishandling) of the pandemic, and results indicated a high level of public discontent related to the rising rates of domestic violence and the lack of services during the pandemic.

conclusionsThis study provided a timely understanding of public sentiment related to domestic violence during the COVID-19 lockdown periods in Australia using social media analysis. Social media represents an important avenue for the dissemination of information; posts can be widely dispersed and easily accessed by a range of different communities who are often difficult to reach. An improved understanding of these issues is important for future policy direction. Heightened awareness of this could help agencies tailor and target messaging to maximize impact.

Indexed as

COVID-19Domestic ViolenceSocial MediaCommunicable Disease ControlHumansPandemicsSARS-CoV-2COVID-19discourse analysisdomestic violencekeyword analysispandemicpublic expressionpublic healthsentimentsentiment analysissocial mediaTwitter

Identifiers

PMID34519659
PMCPMC8489563
OpenAlexW3197456343

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.