# Public Sentiment Analysis of Traffic Management Policies in Knoxville: A Social Media Driven Study

arXiv: https://arxiv.org/abs/2512.03103 · HTML: https://mlsanity.com/paper/2512.03103/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 13 references that are in the map.
- First posted on arXiv 1 Dec 2025.

## Built on by (most cited first, 2 of 2)

- [AgenticCyber: A GenAI-Powered Multi-Agent System for Multimodal Threat Detection and Adaptive Response in Cybersecurity](https://mlsanity.com/paper/2512.06396/) (2025)
- [From Sentiment to Actionable Insights: Public Sentiment Analysis of Advanced Air Mobility](https://mlsanity.com/paper/2606.20751/) (2026)

## Abstract (arXiv)

This study presents a comprehensive analysis of public sentiment toward traffic management policies in Knoxville, Tennessee, utilizing social media data from Twitter and Reddit platforms. We collected and analyzed 7906 posts spanning January 2022 to December 2023, employing Valence Aware Dictionary and sEntiment Reasoner (VADER) for sentiment analysis and Latent Dirichlet Allocation (LDA) for topic modeling. Our findings reveal predominantly negative sentiment, with significant variations across platforms and topics. Twitter exhibited more negative sentiment compared to Reddit. Topic modeling identified six distinct themes, with construction-related topics showing the most negative sentiment while general traffic discussions were more positive. Spatiotemporal analysis revealed geographic and temporal patterns in sentiment expression. The research demonstrates social media's potential as a real-time public sentiment monitoring tool for transportation planning and policy evaluation.