Evidence map›Paper›PMID 34254941›Full record

ArticleJMIR medical informatics2021

Social Media Opinions on Working From Home in the United States During the COVID-19 Pandemic: Observational Study.

Ziyu Xiong, Pin Li, Hanjia Lyu, Jiebo Luo

Abstract read
In one paragraph

Article in JMIR medical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Caregiver Faculty: Working through a Pandemic.Journal of applied social science · 2023
    Article
  3. Review
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

4 authors.

Ziyu XiongUniversity of Rochester, Rochester, NY, United States.ORCID https://orcid.org/0000-0002-0727-7577
Pin LiUniversity of Rochester, Rochester, NY, United States.ORCID https://orcid.org/0000-0001-7155-9598
Hanjia LyuUniversity of Rochester, Rochester, NY, United States.ORCID https://orcid.org/0000-0002-3876-0094
Jiebo LuoUniversity of Rochester, Rochester, NY, United States.ORCID https://orcid.org/0000-0002-4516-9729

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSince March 2020, companies nationwide have started work from home (WFH) owing to the rapid increase of confirmed COVID-19 cases in an attempt to help prevent the disease from spreading and to rescue the economy from the pandemic. Many organizations have conducted surveys to understand people's opinions toward WFH. However, the findings are limited owing to a small sample size and the dynamic topics over time.

objectiveThis study aims to understand public opinions regarding WFH in the United States during the COVID-19 pandemic.

methodsWe conducted a large-scale social media study using Twitter data to portray different groups of individuals who have positive or negative opinions on WFH. We performed an ordinary least squares regression analysis to investigate the relationship between the sentiment about WFH and user characteristics including gender, age, ethnicity, median household income, and population density. To better understand the public opinion, we used latent Dirichlet allocation to extract topics and investigate how tweet contents are related to people's attitude.

resultsOn performing ordinary least squares regression analysis using a large-scale data set of publicly available Twitter posts (n=28,579) regarding WFH during April 10-22, 2020, we found that the sentiment on WFH varies across user characteristics. In particular, women tend to be more positive about WFH (P<.001). People in their 40s are more positive toward WFH than those in other age groups (P<.001). People from high-income areas are more likely to have positive opinions about WFH (P<.001). These nuanced differences are supported by a more fine-grained topic analysis. At a higher level, we found that the most negative sentiment about WFH roughly corresponds to the discussion on government policy. However, people express a more positive sentiment when discussing topics on "remote work or study" and "encouragement." Furthermore, topic distributions vary across different user groups. Women pay more attention to family activities than men (P<.05). Older people talk more about work and express a more positive sentiment regarding WFH.

conclusionsThis paper presents a large-scale social media-based study to understand the public opinion on WFH in the United States during the COVID-19 pandemic. We hope that this study can contribute to policymaking both at the national and institution or company levels to improve the overall population's experience with WFH.

Indexed as

characterizationCOVID-19social mediatopic modelingTwitterwork from home

Identifiers

PMID34254941
PMCPMC8330633

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LicenceCC BY
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Registered trials

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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.