The effect of technological innovation on taxi-driver profession:public social cognition and sentiment polarity based on"Apollo Go"incident
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 under-standing 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 22 835 comments on major Chinese social media platforms,such as Sina Weibo,TikTok,and Little Red Book,we extracted 6 228 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 sen-timent 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 differ-ent provinces formed four distinct categories in terms of sentiment polarity and participation for Top-ics 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 liveli-hood)and Topic 2(order volume).The findings provide empirical evidence for policy makers to bal-ance the social impact resulting from the advancement of robotaxis,thereby contributing to the pro-motion of social harmony and the stable development of the industry.
国家科技期刊平台
NSTL
万方数据
