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How about electric vehicle? Sensing owners’ experiences and attitudes through online short video

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  • Cui, Qinyu
  • Zhang, Yan
  • Ma, Haoran
  • Zhang, Kaihan
  • Peng, Jinhan
  • Chen, Zemu
  • Lin, Peiqun
  • Lin, Zhenhong

Abstract

Understanding the experiences and attitudes of electric vehicle (EV) owners is crucial for driving EV sales and thus promoting a sustainable environment. Previous studies have used costly and inflexible crowdsourced questionnaires to assess EV owner satisfaction. This study adopts an innovative approach by analyzing 41 h of video interviews with 2101 EV owners from a short video platform. Utilizing the Latent Dirichlet Allocation (LDA) model, topics of concern for EV owners were identified, followed by sentiment analysis supported by a large language model (LLM) and random forest model. The results indicate that 1) “After-sales & Brand (19.75 %),” “Performance Experience (25.63 %),” “Functionality & Comfort (31.76 %),” and “Car Cost (22.86 %)” are the four main concerns of EV owners. Notably, concern for car costs is rising, while after-sales service is decreasing. 2) While EV ownership is mostly male, female owners exhibit a higher percentage of positive sentiment, with 47.16 % compared to 36.81 % for male owners. 3) “Functionality & Comfort” is the key satisfaction factor for both genders, then women prioritizing “After-sales and Brand” and men prioritizing “Performance Experience” as secondary concerns. This study proposes a new research framework and empirical case based on short-video data, offering valuable insights for potential consumers and automakers.

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  • Cui, Qinyu & Zhang, Yan & Ma, Haoran & Zhang, Kaihan & Peng, Jinhan & Chen, Zemu & Lin, Peiqun & Lin, Zhenhong, 2025. "How about electric vehicle? Sensing owners’ experiences and attitudes through online short video," Transport Policy, Elsevier, vol. 167(C), pages 1-15.
  • Handle: RePEc:eee:trapol:v:167:y:2025:i:c:p:1-15
    DOI: 10.1016/j.tranpol.2025.03.012
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    1. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    2. Christian M Alis & May T Lim & Helen Susannah Moat & Daniele Barchiesi & Tobias Preis & Steven R Bishop, 2015. "Quantifying Regional Differences in the Length of Twitter Messages," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-10, April.
    3. Archer, Kellie J. & Kimes, Ryan V., 2008. "Empirical characterization of random forest variable importance measures," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 2249-2260, January.
    4. Lin, Boqiang & Shi, Lei, 2024. "Identify the policy weaknesses in China's electric vehicle development," Transport Policy, Elsevier, vol. 157(C), pages 167-178.
    5. Sheldon, Tamara L. & Dua, Rubal, 2020. "Effectiveness of China's plug-in electric vehicle subsidy," Energy Economics, Elsevier, vol. 88(C).
    6. Sun, Lishan & Huang, Yuchen & Liu, Shuli & Chen, Yanyan & Yao, Liya & Kashyap, Anil, 2017. "A completive survey study on the feasibility and adaptation of EVs in Beijing, China," Applied Energy, Elsevier, vol. 187(C), pages 128-139.
    7. Viet Nguyen-Tien & Chengyu Zhang & Eric Strobl & Robert J. R. Elliott, 2025. "The closing longevity gap between battery electric vehicles and internal combustion vehicles in Great Britain," Nature Energy, Nature, vol. 10(3), pages 354-364, March.
    8. Costa, C.M. & Barbosa, J.C. & Castro, H. & Gonçalves, R. & Lanceros-Méndez, S., 2021. "Electric vehicles: To what extent are environmentally friendly and cost effective? – Comparative study by european countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    9. Matthews, Lindsay & Lynes, Jennifer & Riemer, Manuel & Del Matto, Tania & Cloet, Nicholas, 2017. "Do we have a car for you? Encouraging the uptake of electric vehicles at point of sale," Energy Policy, Elsevier, vol. 100(C), pages 79-88.
    10. United Nations UN, 2015. "Transforming our World: the 2030 Agenda for Sustainable Development," Working Papers id:7559, eSocialSciences.
    11. Naseri, Hamed & Waygood, E.O.D. & Patterson, Zachary & Wang, Bobin, 2024. "Who is more likely to buy electric vehicles?," Transport Policy, Elsevier, vol. 155(C), pages 15-28.
    12. Xiao, Quan & Huang, Weiling & Qu, Lu & Li, Xia, 2025. "The impact of multimodal information features of short sales videos on consumer engagement behavior: A multi-method approach," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
    13. Debnath, Ramit & Bardhan, Ronita & Reiner, David M. & Miller, J.R., 2021. "Political, economic, social, technological, legal and environmental dimensions of electric vehicle adoption in the United States: A social-media interaction analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    14. Zou, Pengyu & Zhang, Bin & Yi, Yi & Wang, Zhaohua, 2024. "How does travel satisfaction affect preference for shared electric vehicles? An empirical study using large-scale monitoring data and online text mining," Transport Policy, Elsevier, vol. 146(C), pages 59-71.
    15. Gulnaz Ivanova & António Carrizo Moreira, 2023. "Antecedents of Electric Vehicle Purchase Intention from the Consumer’s Perspective: A Systematic Literature Review," Sustainability, MDPI, vol. 15(4), pages 1-27, February.
    16. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    17. Zhao, Danting & Liu, Yuandong & Zhu, Shaoxuan & Chi, Jinglei, 2025. "Determinants of mini-electric vehicle adoption: Insights from early-adopters in China," Transport Policy, Elsevier, vol. 163(C), pages 298-309.
    18. Jaiswal, Deepak & Deshmukh, Arun Kumar & Thaichon, Park, 2022. "Who will adopt electric vehicles? Segmenting and exemplifying potential buyer heterogeneity and forthcoming research," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    19. Yang, Linchuan & Ao, Yibin & Ke, Jintao & Lu, Yi & Liang, Yuan, 2021. "To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults," Journal of Transport Geography, Elsevier, vol. 94(C).
    20. Champahom, Thanapong & Wisutwattanasak, Panuwat & Chonsalasin, Dissakoon & Se, Chamroeun & Jomnonkwao, Sajjakaj & Ratanavaraha, Vatanavongs, 2025. "Comparing Electric Vehicle Adoption Intentions Across Vehicle Types in Thailand: An Extended UTAUT2 Model with Government Participation," Transport Policy, Elsevier, vol. 163(C), pages 408-435.
    21. Echaniz, Eneko & Cordera, Rubén & Rodriguez, Andrés & Nogués, Soledad & Coppola, Pierlugi & dell’Olio, Luigi, 2022. "Spatial and temporal variation of user satisfaction in public transport systems," Transport Policy, Elsevier, vol. 117(C), pages 88-97.
    22. Scott Hardman & Gil Tal, 2021. "Understanding discontinuance among California’s electric vehicle owners," Nature Energy, Nature, vol. 6(5), pages 538-545, May.
    23. Luo, Shuli & He, Sylvia Y. & Grant-Muller, Susan & Song, Linqi, 2023. "Influential factors in customer satisfaction of transit services: Using crowdsourced data to capture the heterogeneity across individuals, space and time," Transport Policy, Elsevier, vol. 131(C), pages 173-183.
    24. Lv, Zhe & Zhao, Wenjia & Liu, Yu & Wu, Jie & Hou, Mutian, 2024. "Impact of perceived value, positive emotion, product coolness and Mianzi on new energy vehicle purchase intention," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    25. Liu, Zhe & Song, Juhyun & Kubal, Joseph & Susarla, Naresh & Knehr, Kevin W. & Islam, Ehsan & Nelson, Paul & Ahmed, Shabbir, 2021. "Comparing total cost of ownership of battery electric vehicles and internal combustion engine vehicles," Energy Policy, Elsevier, vol. 158(C).
    26. Shanjun Li & Xianglei Zhu & Yiding Ma & Fan Zhang & Hui Zhou, 2022. "The Role of Government in the Market for Electric Vehicles: Evidence from China," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(2), pages 450-485, March.
    27. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    28. Tan, Kang Miao & Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Mansor, Muhamad & Teh, Jiashen & Guerrero, Josep M., 2023. "Factors influencing global transportation electrification: Comparative analysis of electric and internal combustion engine vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    29. Priessner, Alfons & Sposato, Robert & Hampl, Nina, 2018. "Predictors of electric vehicle adoption: An analysis of potential electric vehicle drivers in Austria," Energy Policy, Elsevier, vol. 122(C), pages 701-714.
    30. Jake M. Hofman & Duncan J. Watts & Susan Athey & Filiz Garip & Thomas L. Griffiths & Jon Kleinberg & Helen Margetts & Sendhil Mullainathan & Matthew J. Salganik & Simine Vazire & Alessandro Vespignani, 2021. "Integrating explanation and prediction in computational social science," Nature, Nature, vol. 595(7866), pages 181-188, July.
    31. Luo, Shuli & He, Sylvia Y., 2021. "Understanding gender difference in perceptions toward transit services across space and time: A social media mining approach," Transport Policy, Elsevier, vol. 111(C), pages 63-73.
    32. Bellizzi, Maria Grazia & Eboli, Laura & Mazzulla, Gabriella & Postorino, Maria Nadia, 2022. "Classification trees for analysing highly educated people satisfaction with airlines’ services," Transport Policy, Elsevier, vol. 116(C), pages 199-211.
    33. Kinsella, L. & Stefaniec, A. & Foley, A. & Caulfield, B., 2023. "Pathways to decarbonising the transport sector: The impacts of electrifying taxi fleets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 174(C).
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