近期公眾對交通運輸的興趣激增：利用微博數據對百度Apollo Go進行情感分析

Recent Surge in Public Interest in Transportation: Sentiment Analysis of Baidu Apollo Go Using Weibo Data

August 19, 2024

作者: Shiqi Wang, Zhouye Zhao, Yuhang Xie, Mingchuan Ma, Zirui Chen, Zeyu Wang, Bohao Su, Wenrui Xu, Tianyi Li

cs.AI

摘要

城市移動和交通系統已被自動駕駛車輛技術的進步深刻改變。來自中國科技巨頭百度的先鋒無人出租車服務百度Apollo Go最近已在北京和武漢等主要城市廣泛部署，引發了更多討論，並展示了城市移動未來的一瞥。 本研究使用混合BERT模型對2024年1月至7月的36,096條微博帖子進行情感分析，探討了中國公眾對Apollo Go的態度。分析顯示，89.56\%與Apollo Go相關的帖子集中在7月。從1月到7月，公眾情緒大多是積極的，但在7月21日成為熱門話題後，負面評論開始增加。 空間分析顯示，高討論密度的省份與Apollo Go運營的省份之間存在著很強的相關性。最初，湖北和廣東主導了在線發帖量，但到了7月，廣東、北京和國際地區已超過了湖北。各省的態度存在顯著差異，新疆和青海表現出樂觀，而西藏和甘肅則對傳統出租車服務的影響表示擔憂。 情感分析顯示，積極評論主要集中在技術應用和個人經驗上，而負面評論則集中在就業機會流失和安全問題上。總之，本研究凸顯了公眾對自動叫車服務的看法存在分歧，為規劃者、政策制定者和服務提供者提供了寶貴的見解。該模型已發布在Hugging Face上，網址為https://huggingface.co/wsqstar/bert-finetuned-weibo-luobokuaipao，並在GitHub上建立了存儲庫，網址為https://github.com/GIStudio/trb2024。

English

Urban mobility and transportation systems have been profoundly transformed by the advancement of autonomous vehicle technologies. Baidu Apollo Go, a pioneer robotaxi service from the Chinese tech giant Baidu, has recently been widely deployed in major cities like Beijing and Wuhan, sparking increased conversation and offering a glimpse into the future of urban mobility. This study investigates public attitudes towards Apollo Go across China using Sentiment Analysis with a hybrid BERT model on 36,096 Weibo posts from January to July 2024. The analysis shows that 89.56\% of posts related to Apollo Go are clustered in July. From January to July, public sentiment was mostly positive, but negative comments began to rise after it became a hot topic on July 21. Spatial analysis indicates a strong correlation between provinces with high discussion intensity and those where Apollo Go operates. Initially, Hubei and Guangdong dominated online posting volume, but by July, Guangdong, Beijing, and international regions had overtaken Hubei. Attitudes varied significantly among provinces, with Xinjiang and Qinghai showing optimism and Tibet and Gansu expressing concerns about the impact on traditional taxi services. Sentiment analysis revealed that positive comments focused on technology applications and personal experiences, while negative comments centered on job displacement and safety concerns. In summary, this study highlights the divergence in public perceptions of autonomous ride-hailing services, providing valuable insights for planners, policymakers, and service providers. The model is published on Hugging Face at https://huggingface.co/wsqstar/bert-finetuned-weibo-luobokuaipao and the repository on GitHub at https://github.com/GIStudio/trb2024.