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Consumer Insight on Driverless Automobile Technology Adoption via Twitter Data: A Sentiment Analytic Approach

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Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation (TDIT 2020)

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Abstract

Technology has sped up the innovation effort in the automobile industry. Further to this automobile innovation such as intelligent climate control, adaptive cruise control, and others, we find in today’s vehicles, it has been predicted that by 2030, there will be driverless vehicles, of which samples are already on the market. The news and the sights of these so-called driverless vehicles have generated mixed reactions, and this motivated our study. Hence the present study focuses on a dataset of tweets associated with driverless vehicles downloaded using the Twitter API. Valence Aware Dictionary and sentiment Reasoner (VADER), a lexicon and rule-based sentiment analysis tool were used in extracting sentiments on the tweets to gauge public opinions about the acceptance and adoption of the driverless vehicles ahead of their launch. The VADER sentiment analysis results, however, show that the general discussion on driverless vehicles was positive. Besides, we generated a word cloud to visually analyze the terms in the dataset to gain further insights and understand the messages conveyed by the tweets in other to enhance the usage and adoption of driverless vehicles. This study will enable self-driving vehicle technology service providers and autonomous vehicle manufacturers to gain more insights on how to transform the transportation sector by investing in research and technology.

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Acknowledgment

This work was supported by the research project NPU I no. MSMT-7778/2019 RVO - Digital Transformation and its Impact on Customer Behaviour and Business Processes in Traditional and Online markets and IGA/CebiaTech/2020/001. The work was further supported by the resources of A.I. Lab at the Faculty of Applied Informatics, Tomas Bata University in Zlin (ailab.fai.utb.cz).

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Authors and Affiliations

  1. Faculty of Management and Economics, Tomas Bata University in Zlin, Mostni 5139, 760 01, Zlin, Czech Republic

    Michael Adu Kwarteng, Alex Ntsiful, Raphael Kwaku Botchway, Michal Pilik & Zuzana Komínková Oplatková

  2. Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stráněmi 4511, 760 05, Zlin, Czech Republic

    Michael Adu Kwarteng, Alex Ntsiful, Raphael Kwaku Botchway, Michal Pilik & Zuzana Komínková Oplatková

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  1. Michael Adu Kwarteng
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Correspondence to Michael Adu Kwarteng .

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Editors and Affiliations

  1. Indian Institute of Management Tiruchira, Tiruchirappalli, India

    Sujeet K. Sharma

  2. Swansea University, Swansea, UK

    Yogesh K. Dwivedi

  3. Indian Institute of Management Nagpur, Nagpur, India

    Bhimaraya Metri

  4. University of Bradford, Bradford, UK

    Nripendra P. Rana

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Kwarteng, M.A., Ntsiful, A., Botchway, R.K., Pilik, M., Oplatková, Z.K. (2020). Consumer Insight on Driverless Automobile Technology Adoption via Twitter Data: A Sentiment Analytic Approach. In: Sharma, S.K., Dwivedi, Y.K., Metri, B., Rana, N.P. (eds) Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation. TDIT 2020. IFIP Advances in Information and Communication Technology, vol 617. Springer, Cham. https://doi.org/10.1007/978-3-030-64849-7_41

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  • DOI: https://doi.org/10.1007/978-3-030-64849-7_41

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