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A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion

In this article, we review existing research on the complementarity of social media data and survey data for the study of public opinion. We start by situating our review in the extensive literature (N = 187) about the uses, challenges, and frameworks related to the use of social media for studying...

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Autores principales: Reveilhac, Maud, Steinmetz, Stephanie, Morselli, Davide
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853237/
https://www.ncbi.nlm.nih.gov/pubmed/35194384
http://dx.doi.org/10.1007/s11042-022-12101-0
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author Reveilhac, Maud
Steinmetz, Stephanie
Morselli, Davide
author_facet Reveilhac, Maud
Steinmetz, Stephanie
Morselli, Davide
author_sort Reveilhac, Maud
collection PubMed
description In this article, we review existing research on the complementarity of social media data and survey data for the study of public opinion. We start by situating our review in the extensive literature (N = 187) about the uses, challenges, and frameworks related to the use of social media for studying public opinion. Based on 187 relevant articles (141 empirical and 46 theoretical) - we identify within the 141 empircal ones six main research approaches concerning the complementarity of both data sources. Results show that the biggest share of the research has focused on how social media can be used to confirm survey findings, especially for election predictions. The main contribution of our review is to detail and classify other growing complementarity approaches, such as comparing both data sources on a given phenomenon, using survey measures as a proxy in social media research, enriching surveys with SMD, recruiting individuals on social media to conduct a second survey phase, and generating new insight on “old” or “under-investigated” topics or theories using SMD. We discuss the advantages and disadvantages associated with each of these approaches in relation to four main research purposes, namely the improvement of validity, sustainability, reliability, and interpretability. We conclude by discussing some limitations of our study and highlighting future paths for research.
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spelling pubmed-88532372022-02-18 A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion Reveilhac, Maud Steinmetz, Stephanie Morselli, Davide Multimed Tools Appl Article In this article, we review existing research on the complementarity of social media data and survey data for the study of public opinion. We start by situating our review in the extensive literature (N = 187) about the uses, challenges, and frameworks related to the use of social media for studying public opinion. Based on 187 relevant articles (141 empirical and 46 theoretical) - we identify within the 141 empircal ones six main research approaches concerning the complementarity of both data sources. Results show that the biggest share of the research has focused on how social media can be used to confirm survey findings, especially for election predictions. The main contribution of our review is to detail and classify other growing complementarity approaches, such as comparing both data sources on a given phenomenon, using survey measures as a proxy in social media research, enriching surveys with SMD, recruiting individuals on social media to conduct a second survey phase, and generating new insight on “old” or “under-investigated” topics or theories using SMD. We discuss the advantages and disadvantages associated with each of these approaches in relation to four main research purposes, namely the improvement of validity, sustainability, reliability, and interpretability. We conclude by discussing some limitations of our study and highlighting future paths for research. Springer US 2022-02-14 2022 /pmc/articles/PMC8853237/ /pubmed/35194384 http://dx.doi.org/10.1007/s11042-022-12101-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Reveilhac, Maud
Steinmetz, Stephanie
Morselli, Davide
A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion
title A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion
title_full A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion
title_fullStr A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion
title_full_unstemmed A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion
title_short A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion
title_sort systematic literature review of how and whether social media data can complement traditional survey data to study public opinion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8853237/
https://www.ncbi.nlm.nih.gov/pubmed/35194384
http://dx.doi.org/10.1007/s11042-022-12101-0
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