Social media and logistics : uncovering challenges and solutions through YouTube data

Background: Logistics challenges, such as driver shortages, are a major global issue, with many countries struggling to find effective solutions. YouTube, as a social networking platform, has a growing user base and is increasingly used not only for entertainment but also for social interaction, such as commenting, searching, and browsing, and it can thus potentially be used as an indicator of the topic under discussion. Methods: This study collects YouTube data containing keywords related to logistics issues-particularly the 2024 problem-and applies natural language processing (NLP) techniques to explore potential solutions. It is the first study to analyze both subtitle and comment data extracted from YouTube audio as large-scale text data in the field of logistics. Results: The analysis identified four primary areas of concern in logistics: time management, driver welfare, technological investment, and policy transparency. Sentiment analysis revealed a predominant negative sentiment in user discussions, highlighting dissatisfaction with current logistics policies and operations. Conclusions: The findings provide new insights that could inform the development of effective logistics policies and improve services for logistics companies while also proposing innovative research methods using NLP.