Evidence map›Paper›PMID 35874448›Full record

ArticleFrontiers in sociology2022

Combining Survey and Social Media Data: Respondents' Opinions on COVID-19 Measures and Their Willingness to Provide Their Social Media Account Information.

Markus Hadler, Beate Klösch, Markus Reiter-Haas, Elisabeth Lex

Abstract read
In one paragraph

Article in Frontiers in sociology, 2022. 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. Review
  3. 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

4 authors.

Markus HadlerDepartment of Sociology, University of Graz, Graz, Austria.
Beate KlöschDepartment of Sociology, University of Graz, Graz, Austria.
Markus Reiter-HaasInstitute of Interactive Systems and Data Science, Graz University of Technology, Graz, Austria.
Elisabeth LexInstitute of Interactive Systems and Data Science, Graz University of Technology, Graz, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research on combining social survey responses and social media posts has shown that the willingness to share social media accounts in surveys depends on the mode of the survey and certain socio-demographics of the respondents. We add new insights to this research by demonstrating that the willingness to share their Facebook and Twitter accounts also depends on the respondents' opinions on specific topics. Furthermore, we extend previous research by actually accessing their social media accounts and checking whether survey responses and tweets are coherent. Our analyses indicate that survey respondents who are willing to share their social media accounts hold more positive attitudes toward COVID-19 measures. The same pattern holds true when comparing their sentiments to a larger Twitter collection. Our results highlight another source of sampling bias when combining survey and social media data: a bias due to specific views, which might be related to social desirability.

Indexed as

COVID-19Facebookpolarizationqualitative content analysissentiment analysissocial mediasurveyTwitter

Identifiers

PMID35874448
PMCPMC9298460

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.