用社交媒体数据分析诺克斯维尔交通政策民意，发现施工相关话题最不满
Public Sentiment Analysis of Traffic Management Policies in Knoxville: A Social Media Driven Study
- 从推特和红迪网抓取7906条帖子，用VADER和LDA分析情绪与主题
- 整体情绪偏负面，推特比红迪网更负面，施工类话题情绪最差
- 可实时监测公众情绪，助力交通政策制定与评估
本研究基于田纳西州诺克斯维尔市的推特和红迪网数据，对公众对交通管理政策的舆论进行综合分析。收集并分析了2022年1月至2023年12月间的7906条帖子，采用情感分析工具VADER及主题建模方法LDA。结果表明公众情绪总体偏负面，且在不同平台与主题间存在显著差异：推特上的负面情绪高于红迪网；施工相关主题情绪最差，而一般交通讨论则相对积极。时空分析揭示了情绪表达在地理与时间上的分布模式。研究证明社交媒体可作为交通规划与政策评估中的实时民意监测工具。
原文摘要 · Abstract (English)
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.
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