How is automated and self-driving vehicle technology presented in the news media?

Praveena Penmetsa, Sunday Okafor, Emmanuel Adanu, Matthew Hudnall, Somayeh Bakhtiari Ramezani, Steven Holiday and Steven Jones

Technology in Society, 2023, vol. 74, issue C

Abstract: The media continues to be a prominent and widely embraced channel for obtaining information on various topics, exerting considerable influence in shaping public opinions. This holds particularly true for the realm of automated vehicles (AVs), as the media consistently covers developments in this field, encompassing both positive aspects such as technological advancements, as well as negative occurrences like incidents involving self-driving cars colliding with pedestrians. The objective of this study was to utilize sentiment analysis techniques to evaluate the portrayal of AV technology in media news coverage. Data was retrieved from Sprinklr using keywords that are often associated with AVs. Over 1.7 million articles were collected on the keywords for relevant articles published between May 1, 2015 to May 24, 2021. Sentiment analysis was carried out on the cleaned data using three different models – VADER, TextBlob, and NRCLex. The sentiment analysis was separately conducted on the title and text of the articles. 2018 recorded the highest number of news articles on the AV technology. The number of negative sentiments in the title of articles published on the web in 2018 increased 12 times compared to the previous year. The negativity induced in 2018 in the news media did not continue in the next year, which explains that the technology experienced short term effects from the negative incidents associated with its early development. The news articles were also found to have subjectivity from the authors in the article text. The findings are expected to stimulate debates among industry players on how to bring the media along the journey of the development and eventual full deployment of AVs.

Keywords: Automated vehicles; Self driving vehicles; Sentiment analysis; Public perception; News; Media (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:teinso:v:74:y:2023:i:c:s0160791x23000957

DOI: 10.1016/j.techsoc.2023.102290

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