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Demographic-Based Public Perception Analysis of Electric Vehicles on Online Social Networks

Author

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  • Tavishi Priyam

    (Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309, USA
    These authors contributed equally to this work.)

  • Tao Ruan

    (Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309, USA
    These authors contributed equally to this work.)

  • Qin Lv

    (Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309, USA)

Abstract

Electric vehicles have gained significant popularity in the market, with sales increasing yearly. The introduction of new policies and reforms aimed at promoting environmental sustainability, coupled with the release of more advanced electric vehicles with higher driving ranges and technical specifications, has encouraged more people to consider switching to electric vehicles. However, there is still a lack of understanding of public perception and the factors influencing the decision to switch to electric vehicles, especially among people from different demographic groups. In this study, we leverage machine learning techniques to analyze public opinion about electric vehicles across different demographic groups on two online social networks (OSNs), namely Reddit and Twitter. Our analyses provide valuable insights into how users on these platforms perceive electric vehicles and the factors that influence their perception. This information can be used to inform market strategies and future policies aimed at promoting the adoption of electric vehicles.

Suggested Citation

  • Tavishi Priyam & Tao Ruan & Qin Lv, 2023. "Demographic-Based Public Perception Analysis of Electric Vehicles on Online Social Networks," Sustainability, MDPI, vol. 16(1), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:305-:d:1309615
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    References listed on IDEAS

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    1. Montgomery, James D, 1991. "Social Networks and Labor-Market Outcomes: Toward an Economic Analysis," American Economic Review, American Economic Association, vol. 81(5), pages 1407-1418, December.
    2. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    3. Tasnim M. A. Zayet & Maizatul Akmar Ismail & Kasturi Dewi Varathan & Rafidah M. D. Noor & Hui Na Chua & Angela Lee & Yeh Ching Low & Sheena Kaur Jaswant Singh, 2021. "Investigating transportation research based on social media analysis: a systematic mapping review," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6383-6421, August.
    4. 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.
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