Natural language processing and text mining in transportation: Current status, challenges, and future roadmap
Published in Expert Systems with Applications, 2025
The transportation sector is generating and accumulating an increasing amount of unstructured data from a variety of sources. As a result, Natural Language Processing (NLP) and text mining are becoming critical for their capability to automatically process and interpret human language in transportation research. However, there is a lack of a thorough review of existing research in this field, as well as a detailed guide on how to use these techniques in transportation studies. This paper offers an updated review of NLP and text mining techniques, including the latest developments in Large Language Models (LLMs), tailored for comprehensive transportation modeling across land, maritime, and aviation sectors. It highlights the data sources and methodologies used in previous studies, provides an analysis of word representation, sentiment analysis, external NLP toolkits, language diversity, and performance …
Recommended citation: X Zhang, R Gao, Z Xiao, K Wang, T Liu, M Liang, J Zhang. (2025). Natural language processing and text mining in transportation: Current status, challenges, and future roadmap. Expert Systems with Applications, 129050. https://www.sciencedirect.com/science/article/pii/S0957417425026673