Investigating The Impacting Factors on The Public's Attitudes Towards Autonomous Vehicles Using Sentiment Analysis from Social Media Data
Shengzhao Wang, Meitang Li, Bo Yu, Shan Bao, Yuren Chen

TL;DR
This study uses large-scale social media data and sentiment analysis to identify key factors influencing public attitudes towards autonomous vehicles, revealing both positive and negative impacts of various topics on acceptance.
Contribution
It introduces a novel approach combining social media data, sentiment analysis, and statistical modeling to comprehensively analyze factors affecting public attitudes towards AVs.
Findings
Public attitude towards AVs is slightly optimistic.
Factors like 'drunk', 'blind spot', and 'mobility' significantly impact attitudes.
Positive feelings are associated with 'lidar' and 'Tesla', while 'COVID-19' and 'pedestrian' negatively affect attitudes.
Abstract
The public's attitudes play a critical role in the acceptance, purchase, use, and research and development of autonomous vehicles (AVs). To date, the public's attitudes towards AVs were mostly estimated through traditional survey data with high labor costs and a low quantity of samples, which also might be one of the reasons why the influencing factors on the public's attitudes of AVs have not been studied from multiple aspects in a comprehensive way yet. To address the issue, this study aims to propose a method by using large-scale social media data to investigate key factors that affect the public's attitudes and acceptance of AVs. A total of 954,151 Twitter data related to AVs and 53 candidate independent variables from seven categories were extracted using the web scraping method. Then, sentiment analysis was used to measure the public attitudes towards AVs by calculating sentiment…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTransportation and Mobility Innovations · Human Mobility and Location-Based Analysis · Human-Automation Interaction and Safety
