Abstract
<title>Abstract</title> <p>In January 2025, New York City has become the first major U.S. city to implement congestion pricing policy. This has sparked significant public debate across social media platforms. This paper analyzes public discourse on congestion pricing across multiple social media platforms (including YouTube, Reddit, and TikTok), since these platforms complement one another in audience and content style. Our datasets comprise 12,365 user-generated comments and posts capturing discourse before and after the policy’s implementation. We employ a multi-stage natural language processing pipeline that integrates automated data collection, video transcript extraction and summarization, multi-dimensional sentiment classification, stance and tone analysis, demographic profiling of social media users, along with a comprehensive set of analysis on temporal evolution, topic analysis, platform polarization, and demographic implications. The notable finding is that overall 43.4% of comments express negative sentiment while 44.8% express opposition to the policy, and public sentiments vary substantially across platforms. Topics like “revenue use” and “impacts on drivers/commuters” show higher levels of skepticism and negative sentiment, whereas benefit-oriented topics exhibit more supportive attitudes. These findings can inform policy making for other U.S. cities that plan to implement congestion pricing, and assist with how transportation agencies communicate and respond to public concerns around congestion pricing.</p>