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How to improve representativeness and cost-effectiveness in samples recruited through meta: A comparison of advertisement tools
The use of paid advertisements on social media, in particular Meta platforms, to create samples for online survey research is becoming increasingly common. In addition to researchers working on hard-to-reach populations, Meta’s promise of unmediated, quick, and cheap access to a large pool of survey...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9907806/ https://www.ncbi.nlm.nih.gov/pubmed/36753470 http://dx.doi.org/10.1371/journal.pone.0281243 |
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author | Neundorf, Anja Öztürk, Aykut |
author_facet | Neundorf, Anja Öztürk, Aykut |
author_sort | Neundorf, Anja |
collection | PubMed |
description | The use of paid advertisements on social media, in particular Meta platforms, to create samples for online survey research is becoming increasingly common. In addition to researchers working on hard-to-reach populations, Meta’s promise of unmediated, quick, and cheap access to a large pool of survey takers across the world is appealing also for researchers who want to create diverse samples of national populations for cheaper prices. Yet the design of Meta’s advertisement optimization algorithm complicates the use of Meta advertisements for this purpose, as it generates a trade-off between cost-effectiveness and sample representativeness. In this paper, we rely on original online surveys conducted in the United Kingdom, Turkey, Spain, and the Czech Republic to explore how two primary tools determining the audience of Meta advertisements, i.e., campaign objectives and demographic targeting, affect the recruitment process, response quality, and sample characteristics. In addition to documenting the trade-offs between the cost and representativeness in Meta samples, our paper also shows that researchers can create high-quality, cost-efficient, and diverse samples if they use the right combination of Meta advertisement tools. |
format | Online Article Text |
id | pubmed-9907806 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-99078062023-02-08 How to improve representativeness and cost-effectiveness in samples recruited through meta: A comparison of advertisement tools Neundorf, Anja Öztürk, Aykut PLoS One Research Article The use of paid advertisements on social media, in particular Meta platforms, to create samples for online survey research is becoming increasingly common. In addition to researchers working on hard-to-reach populations, Meta’s promise of unmediated, quick, and cheap access to a large pool of survey takers across the world is appealing also for researchers who want to create diverse samples of national populations for cheaper prices. Yet the design of Meta’s advertisement optimization algorithm complicates the use of Meta advertisements for this purpose, as it generates a trade-off between cost-effectiveness and sample representativeness. In this paper, we rely on original online surveys conducted in the United Kingdom, Turkey, Spain, and the Czech Republic to explore how two primary tools determining the audience of Meta advertisements, i.e., campaign objectives and demographic targeting, affect the recruitment process, response quality, and sample characteristics. In addition to documenting the trade-offs between the cost and representativeness in Meta samples, our paper also shows that researchers can create high-quality, cost-efficient, and diverse samples if they use the right combination of Meta advertisement tools. Public Library of Science 2023-02-08 /pmc/articles/PMC9907806/ /pubmed/36753470 http://dx.doi.org/10.1371/journal.pone.0281243 Text en © 2023 Neundorf, Öztürk https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Neundorf, Anja Öztürk, Aykut How to improve representativeness and cost-effectiveness in samples recruited through meta: A comparison of advertisement tools |
title | How to improve representativeness and cost-effectiveness in samples recruited through meta: A comparison of advertisement tools |
title_full | How to improve representativeness and cost-effectiveness in samples recruited through meta: A comparison of advertisement tools |
title_fullStr | How to improve representativeness and cost-effectiveness in samples recruited through meta: A comparison of advertisement tools |
title_full_unstemmed | How to improve representativeness and cost-effectiveness in samples recruited through meta: A comparison of advertisement tools |
title_short | How to improve representativeness and cost-effectiveness in samples recruited through meta: A comparison of advertisement tools |
title_sort | how to improve representativeness and cost-effectiveness in samples recruited through meta: a comparison of advertisement tools |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9907806/ https://www.ncbi.nlm.nih.gov/pubmed/36753470 http://dx.doi.org/10.1371/journal.pone.0281243 |
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