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Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study
A recurrent criticism concerning the use of online social media data in political science research is the lack of demographic information about social media users. By employing a face-recognition algorithm to the profile pictures of Facebook users, the paper derives two fundamental demographic chara...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347201/ https://www.ncbi.nlm.nih.gov/pubmed/30682111 http://dx.doi.org/10.1371/journal.pone.0211013 |
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author | Mancosu, Moreno Bobba, Giuliano |
author_facet | Mancosu, Moreno Bobba, Giuliano |
author_sort | Mancosu, Moreno |
collection | PubMed |
description | A recurrent criticism concerning the use of online social media data in political science research is the lack of demographic information about social media users. By employing a face-recognition algorithm to the profile pictures of Facebook users, the paper derives two fundamental demographic characteristics (age and gender) of a sample of Facebook users who interacted with the most relevant British parties in the two weeks before the Brexit referendum of 23 June 2016. The article achieves the goals of (i) testing the precision of the algorithm, (ii) testing its validity, (iii) inferring new evidence on digital mobilisation, and (iv) tracing the path for future developments and application of the algorithm. The findings show that the algorithm is reliable and that it can be fruitfully used in political and social sciences both to confirm the validity of survey data and to obtain information from populations that are generally unavailable within traditional surveys. |
format | Online Article Text |
id | pubmed-6347201 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-63472012019-02-02 Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study Mancosu, Moreno Bobba, Giuliano PLoS One Research Article A recurrent criticism concerning the use of online social media data in political science research is the lack of demographic information about social media users. By employing a face-recognition algorithm to the profile pictures of Facebook users, the paper derives two fundamental demographic characteristics (age and gender) of a sample of Facebook users who interacted with the most relevant British parties in the two weeks before the Brexit referendum of 23 June 2016. The article achieves the goals of (i) testing the precision of the algorithm, (ii) testing its validity, (iii) inferring new evidence on digital mobilisation, and (iv) tracing the path for future developments and application of the algorithm. The findings show that the algorithm is reliable and that it can be fruitfully used in political and social sciences both to confirm the validity of survey data and to obtain information from populations that are generally unavailable within traditional surveys. Public Library of Science 2019-01-25 /pmc/articles/PMC6347201/ /pubmed/30682111 http://dx.doi.org/10.1371/journal.pone.0211013 Text en © 2019 Mancosu, Bobba http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 Mancosu, Moreno Bobba, Giuliano Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study |
title | Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study |
title_full | Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study |
title_fullStr | Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study |
title_full_unstemmed | Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study |
title_short | Using deep-learning algorithms to derive basic characteristics of social media users: The Brexit campaign as a case study |
title_sort | using deep-learning algorithms to derive basic characteristics of social media users: the brexit campaign as a case study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347201/ https://www.ncbi.nlm.nih.gov/pubmed/30682111 http://dx.doi.org/10.1371/journal.pone.0211013 |
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