Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115563
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.contributorResearch Institute for Sustainable Urban Development-
dc.contributorOtto Poon Charitable Foundation Smart Cities Research Institute-
dc.contributorMainland Development Office-
dc.creatorLi, Y-
dc.creatorTang, JHCG-
dc.creatorWang, S-
dc.creatorPeng, Z-
dc.creatorZhuge, C-
dc.date.accessioned2025-10-08T01:16:28Z-
dc.date.available2025-10-08T01:16:28Z-
dc.identifier.issn0049-4488-
dc.identifier.urihttp://hdl.handle.net/10397/115563-
dc.language.isoenen_US
dc.publisherSpringer New York LLCen_US
dc.rights© The Author(s) 2025en_US
dc.rightsOpen Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Li, Y., Tang, J.H.C.G., Wang, S. et al. Attention and attitudes of Chinese social media users towards autonomous vehicles: sentimental, statistical and spatiotemporal perspectives. Transportation (2025) is available at https://doi.org/10.1007/s11116-025-10644-3.en_US
dc.subjectAutonomous vehicleen_US
dc.subjectPublic attentionen_US
dc.subjectSocial mediaen_US
dc.subjectText miningen_US
dc.titleAttention and attitudes of Chinese social media users towards autonomous vehicles : sentimental, statistical and spatiotemporal perspectivesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1007/s11116-025-10644-3-
dcterms.abstractIn recent years, autonomous driving technology has progressed rapidly, promising to transform current transportation systems significantly and attracting growing public attention. Previous studies have predominantly relied on interviews and surveys to examine public perceptions of autonomous vehicles (AVs), which come with inherent limitations. This study utilizes a substantial dataset of 616,355 samples from Sina Weibo, one of China’s most prominent social media platforms, to examine variations in statistical, temporal, spatial, and emotional dimensions to gain insights into the Chinese populace’s perceptions and sentiments towards AVs. From 2015 to 2023, public attention and engagement have steadily risen, with individual users representing the largest group interested in AVs. Among individual users, males and young adults (aged 18–30) have demonstrated heightened interest. Attention levels are particularly pronounced in economically developed regions such as Beijing, Guangdong, and Shanghai. Overall, the public attitude towards AVs is positive; however, there has been a significant rise in negative sentiment since 2020, primarily related to concerns about safety and technological reliability. Based on public attention, this study also discusses potential challenges and corresponding strategies. These insights gained will aid automobile manufacturers, technology firms, and public agencies in addressing emerging challenges and facilitating the development of AVs.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTransportation, Published: 25 June 2025, Online first articles, https://doi.org/10.1007/s11116-025-10644-3-
dcterms.isPartOfTransportation-
dcterms.issued2025-
dc.identifier.scopus2-s2.0-105008956709-
dc.identifier.eissn1572-9435-
dc.description.validate202510 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TAen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextWe thank the Shenzhen Park of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone. This research was funded by the “Theories for Spatiotemporal Intelligence and Reliable Data Analysis” (Project ID: HZQSWS-KCCYB-2024058), the RISUD Joint Research Fund (Grant Number: 1-BBWR) and CRW-SC (Grant Number: U-CDB9) at the Hong Kong Polytechnic University.en_US
dc.description.pubStatusEarly releaseen_US
dc.description.TASpringer Nature (2025)en_US
dc.description.oaCategoryTAen_US
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