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公众对数字时尚的认知：情感分析与潜在狄利克雷分配主题建模

Public perceptions of digital fashion: An analysis of sentiment and Latent Dirichlet Allocation topic modeling.

作者信息

Zou Yixin, Luh Ding-Bang, Lu Shizhu

机构信息

School of Art and Design, Guangdong University of Technology, Guangzhou, China.

出版信息

Front Psychol. 2022 Dec 28;13:986838. doi: 10.3389/fpsyg.2022.986838. eCollection 2022.

DOI:10.3389/fpsyg.2022.986838
PMID:36643702
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9832026/
Abstract

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.

摘要

由于数字技术对时尚产业产生了重大影响，数字时尚已成为当今社会的热门话题。目前，关于数字时尚的研究主要集中在企业营销策略的转变以及数字技术的探讨上。尽管如此，当前的研究并未包括对社交网络平台上受众对数字时尚的情感和认知反应的分析。本研究使用k均值聚类分析、潜在狄利克雷分配（LDA）主题建模和情感分析，对社交网站上发布的52,891篇关于数字时尚和虚拟时尚的帖子进行了全面分析和讨论。该研究考察了公众对数字时尚的认知和热门话题，以及该行业的发展状况和趋势。研究结果显示，公众对数字时尚的态度伴随着积极和中性的情绪。讨论涵盖了广泛的话题。数字技术的创新已经影响了时尚相关企业的就业创造、人才需求、营销策略、盈利形式和产业链创新。相关领域的研究人员不仅会发现本研究对研究方法和方向具有参考价值，而且也是研究方法论的参考来源。同时也将为行业从业者提供案例研究和数据参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/c61e1a764bcb/fpsyg-13-986838-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/0c6230605057/fpsyg-13-986838-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/ce00efa65a1f/fpsyg-13-986838-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/8290234a2e88/fpsyg-13-986838-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/124c3a8f479a/fpsyg-13-986838-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/6503ac3bc131/fpsyg-13-986838-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/7ee72a73c1a5/fpsyg-13-986838-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/c61e1a764bcb/fpsyg-13-986838-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/0c6230605057/fpsyg-13-986838-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/ce00efa65a1f/fpsyg-13-986838-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/8290234a2e88/fpsyg-13-986838-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/124c3a8f479a/fpsyg-13-986838-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/6503ac3bc131/fpsyg-13-986838-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/7ee72a73c1a5/fpsyg-13-986838-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2458/9832026/c61e1a764bcb/fpsyg-13-986838-g007.jpg

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