Evidence map›Paper›PMID 36726996›Full record

ArticleFrontiers in big data2022

Sharing social media data: The role of past experiences, attitudes, norms, and perceived behavioral control.

Esra Akdeniz, Kerrin Emilia Borschewski, Johannes Breuer, Yevhen Voronin

Abstract read
In one paragraph

Article in Frontiers in big data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Esra AkdenizData Services for the Social Sciences, GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany.
Kerrin Emilia BorschewskiData Services for the Social Sciences, GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany.
Johannes BreuerSurvey Data Curation, GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany.
Yevhen VoroninData Services for the Social Sciences, GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social media data (SMD) have become an important data source in the social sciences. The purpose of this paper is to investigate the experiences and practices of researchers working with SMD in their research and gain insights into researchers' sharing behavior and influencing factors for their decisions. To achieve these aims, we conducted a survey study among researchers working with SMD. The questionnaire covered different topics related to accessing, (re)using, and sharing SMD. To examine attitudes toward data sharing, perceived subjective norms, and perceived behavioral control, we used questions based on the Theory of Planned Behavior (TPB). We employed a combination of qualitative and quantitative analyses. The results of the qualitative analysis show that the main reasons for not sharing SMD were that sharing was not considered or needed, as well as legal and ethical challenges. The quantitative analyses reveal that there are differences in the relative importance of past sharing and reuse experiences, experienced challenges, attitudes, subjective norms, and perceived behavioral control as predictors of future SMD sharing intentions, depending on the way the data should be shared (publicly, with restricted access, or upon personal request). Importantly, the TPB variables have predictive power for all types of SMD sharing.

Indexed as

data managementdata reusedata sharingsocial media dataTheory of Planned Behavior

Identifiers

PMID36726996
PMCPMC9885192

What OpenQuestion holds

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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.