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利用2010年至2022年社交媒体数据对日本老年驾驶员的公众话语进行纵向分析

Public Discourse Toward Older Drivers in Japan Using Social Media Data From 2010 to 2022: Longitudinal Analysis.

作者信息

Nakanishi Akito, Ichikawa Masao, Sano Yukie

机构信息

Graduate School of Science and Technology, University of Tsukuba, Ibaraki, Japan.

Institute of Medicine, University of Tsukuba, Ibaraki, Japan.

出版信息

JMIR Infodemiology. 2025 Jun 16;5:e69321. doi: 10.2196/69321.

Abstract

BACKGROUND

As the global population ages, concerns about older drivers are intensifying. Although older drivers are not inherently more dangerous than other age groups, traditional surveys in Japan reveal persistent negative sentiments toward them. This discrepancy suggests the importance of analyzing discourse on social media, where public perceptions and societal attitudes toward older drivers are actively shaped.

OBJECTIVE

This study aimed to quantify long-term public discourse on older drivers in Japan through Twitter (subsequently rebranded X), a leading social media platform. The specific objectives were to (1) examine the sentiments toward older drivers in tweets, (2) identify the textual contents and topics discussed in the tweets, and (3) analyze how sentiments correlate with various variables.

METHODS

We collected Japanese tweets related to older drivers from 2010 to 2022. Each quarter, we (1) applied to the Japanese version of the Linguistic Inquiry and Word Count dictionary for sentiment analysis, (2) employed 2-layer nonnegative matrix factorization for dynamic topic modeling, and (3) applied correlation analyses to explore the relationships of sentiments with crash rates, data counts, and topics.

RESULTS

We obtained 2,625,807 tweets from 1,052,976 unique users discussing older drivers. The number of tweets has steadily increased, with significant peaks in 2016, 2019, and 2021, coinciding with high-profile traffic crashes. Sentiment analysis revealed a predominance of negative emotions (n=383,520, 62.42%), anger (n=106,767, 17.38%), anxiety (n=114,234, 18.59%), and risk (n=357,311, 58.15%). Topic modeling identified 29 dynamic topics, including those related to driving licenses, crash events, self-driving technology, and traffic safety. The crash events topic, which increased by 0.28% per year, showed a strong correlation with negative emotion (r=0.76, P<.001) and risk (r=0.72, P<.001).

CONCLUSIONS

This 13-year study quantified public discourse on older drivers using Twitter data, revealing a paradoxical increase in negative sentiment and perceived risk, despite a decline in the actual crash rate among older drivers. These findings underscore the importance of reconsidering licensing policies, promoting self-driving systems, and fostering a more balanced understanding to mitigate undue prejudice and support continued safe mobility for older adults.

摘要

背景

随着全球人口老龄化,对老年驾驶者的担忧日益加剧。尽管老年驾驶者本质上并不比其他年龄组更危险,但日本的传统调查显示,人们对他们一直存在负面情绪。这种差异表明,分析社交媒体上的言论很重要,因为公众对老年驾驶者的看法和社会态度在社交媒体上正在积极形成。

目的

本研究旨在通过领先的社交媒体平台推特(后更名为X)量化日本关于老年驾驶者的长期公众言论。具体目标是:(1)检查推文中对老年驾驶者的情绪;(2)识别推文中讨论的文本内容和话题;(3)分析情绪与各种变量之间的相关性。

方法

我们收集了2010年至2022年与老年驾驶者相关的日语推文。每季度,我们:(1)应用日语版的语言查询与字数统计词典进行情绪分析;(2)采用两层非负矩阵分解进行动态话题建模;(3)应用相关性分析来探索情绪与撞车率、数据数量和话题之间的关系。

结果

我们从1,052,976名独特用户那里获得了2,625,807条讨论老年驾驶者的推文。推文数量稳步增加,在2016年、2019年和2021年出现显著峰值,与引人注目的交通事故同时发生。情绪分析显示负面情绪占主导(n = 383,520,62.42%),愤怒(n = 106,767,17.38%)、焦虑(n = 114,234,18.59%)和风险(n = 357,311,58.15%)。话题建模识别出29个动态话题,包括与驾驶执照、撞车事件、自动驾驶技术和交通安全相关的话题。撞车事件话题每年增长0.28%,与负面情绪(r = 0.76,P <.001)和风险(r = 0.72,P <.001)显示出强烈相关性。

结论

这项为期13年的研究利用推特数据量化了关于老年驾驶者的公众言论,揭示了一个矛盾现象:尽管老年驾驶者的实际撞车率有所下降,但负面情绪和感知风险却在增加。这些发现强调了重新考虑驾照政策、推广自动驾驶系统以及培养更平衡理解的重要性,以减轻不当偏见并支持老年人持续安全出行。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4cf/12209477/d554fa0bc567/infodemiology-v5-e69321-g001.jpg

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