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Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling
Since digital technology has had a significant impact on the fashion industry, digital fashion has become a hot topic in today’s society. Currently, research on digital fashion is focused on the transformation of enterprise marketing strategies and the discussion of digital technology. Despite this,...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832026/ https://www.ncbi.nlm.nih.gov/pubmed/36643702 http://dx.doi.org/10.3389/fpsyg.2022.986838 |
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author | Zou, Yixin Luh, Ding-Bang Lu, Shizhu |
author_facet | Zou, Yixin Luh, Ding-Bang Lu, Shizhu |
author_sort | Zou, Yixin |
collection | PubMed |
description | Since digital technology has had a significant impact on the fashion industry, digital fashion has become a hot topic in today’s society. Currently, research on digital fashion is focused on the transformation of enterprise marketing strategies and the discussion of digital technology. Despite this, the current study does not include an analysis of the audience’s emotional and cognitive responses to digital fashion on social networking platforms. A comprehensive analysis and discussion of 52,891 posts about digital fashion and virtual fashion published on social networking sites was conducted using k-means clustering analysis, Latent Dirichlet Allocation (LDA) topic modeling, and sentiment analysis in this study. The study examines the public’s perception and hot topics about digital fashion, as well as the industry’s development situation and trends. According to the findings, both positive and neutral emotions accompany the public’s attitude toward digital fashion. There is a wide range of topics covered in the discussion. Innovations in digital technology have impacted the creation of jobs, talent demand, marketing strategies, profit forms, and industrial chain innovation of fashion-related businesses. Researchers in related fields will find this study useful not only as a reference for research methods and directions, but also as a source of references for research methodology. A case study and data reference will also be provided to industry practitioners. |
format | Online Article Text |
id | pubmed-9832026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98320262023-01-12 Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling Zou, Yixin Luh, Ding-Bang Lu, Shizhu Front Psychol Psychology Since digital technology has had a significant impact on the fashion industry, digital fashion has become a hot topic in today’s society. Currently, research on digital fashion is focused on the transformation of enterprise marketing strategies and the discussion of digital technology. Despite this, the current study does not include an analysis of the audience’s emotional and cognitive responses to digital fashion on social networking platforms. A comprehensive analysis and discussion of 52,891 posts about digital fashion and virtual fashion published on social networking sites was conducted using k-means clustering analysis, Latent Dirichlet Allocation (LDA) topic modeling, and sentiment analysis in this study. The study examines the public’s perception and hot topics about digital fashion, as well as the industry’s development situation and trends. According to the findings, both positive and neutral emotions accompany the public’s attitude toward digital fashion. There is a wide range of topics covered in the discussion. Innovations in digital technology have impacted the creation of jobs, talent demand, marketing strategies, profit forms, and industrial chain innovation of fashion-related businesses. Researchers in related fields will find this study useful not only as a reference for research methods and directions, but also as a source of references for research methodology. A case study and data reference will also be provided to industry practitioners. Frontiers Media S.A. 2022-12-28 /pmc/articles/PMC9832026/ /pubmed/36643702 http://dx.doi.org/10.3389/fpsyg.2022.986838 Text en Copyright © 2022 Zou, Luh and Lu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Zou, Yixin Luh, Ding-Bang Lu, Shizhu Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling |
title | Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling |
title_full | Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling |
title_fullStr | Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling |
title_full_unstemmed | Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling |
title_short | Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling |
title_sort | public perceptions of digital fashion: an analysis of sentiment and latent dirichlet allocation topic modeling |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9832026/ https://www.ncbi.nlm.nih.gov/pubmed/36643702 http://dx.doi.org/10.3389/fpsyg.2022.986838 |
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