Analyzing Public Disputation of Autonomous Driving Technology: A Study Based on Data Mining

With the rapid development of autonomous driving technology, public’s opinion of this technology shows diversification and complexity. The discussion about autonomous driving online has a large quantity and diverse perspectives, which causes the traditional data analysis methods hard to catch and understand the whole spectrum of these data. This paper explores how to use text mining techniques effectively, especially the Latent Dirichlet Allocation (LDA) model, to analyze and understand people’s attitude and viewpoint towards autonomous driving technology. By calculating the perplexity, coherence, Jensen-Shannon (JS)divergence and other related parameter indicators of the LDA model, striving to obtain the text mining model with best performance, in order to get valuable information faster and more efficiently.