Public Perception Toward Tesla Fatal Accidents: Neural Network Approach

This study endeavors to comprehensively evaluate the impact that fatal accidents involving autonomous vehicles, with a focus on incidents associated with Tesla, have on the public's perception of this technology. To achieve this, we systematically collect and examine user interactions on Twitter, encompassing the period both before and after such accidents occur. By employing a sophisticated Siamese neural network model for our analysis, we are able to effectively identify and quantify shifts in public sentiment and discourse regarding autonomous vehicles. The results of our investigation reveal a nuanced landscape of public opinion, characterized by a significant alteration in perception following these incidents. Specifically, our findings delineate a complex dynamic where, alongside an increased acceptance of autonomous vehicle technology, there exists a persistent and substantial concern regarding its safety and reliability. This study not only sheds light on the immediate reaction of the public to fatal accidents involving autonomous vehicles but also contributes to a deeper understanding of the broader societal implications of adopting such technology. Through this analysis, we underscore the importance of addressing public safety concerns and enhancing communication strategies to foster a more informed and balanced discourse around the future of autonomous vehicle technology.