技术革新对出租车司机职业的冲击:“萝卜快跑”事件下的公众社会认知与情感倾向  

The effect of technological innovation on taxi-driver profession:public social cognition and sentiment polarity based on“Apollo Go”incident

作　　者：孙慧倩 景鹏[1] 贺正冰 汪道歌 徐佳欣 姜乐炜 SUN Huiqian;JING Peng;HE Zhengbing;WANG Daoge;XU Jiaxin;JIANG Lewei(School of Automobile and Traffic Engineering,Jiangsu University,Zhenjiang 212013,China;Department of Urban Studies and Planning,Massachusetts Institute of Technology,Cambridge 2139-4307,USA)

机构地区：[1]江苏大学,汽车与交通工程学院,镇江212013 [2]麻省理工学院,信息与决策系统实验室,美国剑桥2139-4307

出　　处：《交通运输工程与信息学报》2024年第4期13-24,共12页Journal of Transportation Engineering and Information

基　　金：国家自然科学基金项目(71871107);江苏省自然科学基金面上项目(BK20231324)。

摘　　要：2024年5月,百度推出的“萝卜快跑”无人驾驶出租车服务在湖北武汉启动了大规模商业化运营。该服务以具有竞争力的定价策略和人力成本优势引发了公众关于无人驾驶出租车与传统出租车和网约车(统称为出租车行业)竞争和利益冲突的激烈讨论。在无人驾驶出租车服务商业化运营初期,深入了解公众对于这一新兴服务对司机职业冲击的认知,对于制定有效政策、避免社会摩擦、促进出租车行业的稳定发展和实现社会和谐具有重要意义。通过对微博、抖音、小红书等中国主要社交媒体平台上的22835条评论进行筛选,我们锁定了6228条与出租车司机直接相关的评论。本研究采用Latent Dirichlet Allocation主题模型,成功提取了公众普遍关注的五个热点主题,并形成了从订单量到技术应用的主题递进链条。情感分析结果显示在“萝卜快跑”事件的影响下,公众对出租车司机职业稳定性的看法普遍带有消极情绪且占据主导地位。K-means聚类分析显示,不同省份在情感倾向和对主题1至5的参与度上形成了四个差异类别。例如,类别2普遍参与到主题3(底层工作者)和主题4(司机失业)的讨论中,而第3类别的省份则更对主题1(家庭生计)和主题2(订单量)表现出较高的关注。上述发现为政策制定者在无人驾驶出租车技术推进中平衡社会影响提供了实证依据,有助于促进社会和谐与行业稳定发展。In May 2024,Baidu’s“Apollo Go”robotaxi services commenced large-scale commercial operations in Wuhan,Hubei Province.Characterized by its competitive pricing strategy and reduced labor costs,the service ignited extensive public discourse regarding the competition and underlying conflicts of interest between robotaxis and the conventional online taxi ride-hailing,collectively known as the taxi industry.At the initial commercialization stage of robotaxi services,a deep understanding of the public’s perception regarding the conflict between this emerging service and the taxi industry is crucial for formulating effective policies.Additionally,social friction can be avoided,thus promoting the stable development of the taxi industry and achieving social harmony.By analyzing 22835 comments on major Chinese social media platforms,such as Sina Weibo,TikTok,and Little Red Book,we extracted 6228 comments directly related to taxi drivers.Additionally,we employed the Latent Dirichlet Allocation topic model to extract the top-five topics of general public concern,thus forming a progressive theme chain from order volume to technology application.Results of sentiment analysis indicate that the public’s views on the job stability of taxi drivers are predominantly negative owing to the“Apollo Go”incident.Results of K-means clustering analysis show that different provinces formed four distinct categories in terms of sentiment polarity and participation for Topics 1 to 5.For instance,Type 2 generally discusses Topic 3(vulnerable workers)and Topic 4(driver unemployment),whereas the provinces in Type 3 show greater concern for Topic 1(family livelihood)and Topic 2(order volume).The findings provide empirical evidence for policy makers to balance the social impact resulting from the advancement of robotaxis,thereby contributing to the promotion of social harmony and the stable development of the industry.

关 键 词：智能交通 公众认知 文本挖掘 出租车司机 无人驾驶出租车 行业冲突 

分 类 号：F572[经济管理—产业经济]