Text Mining of South Korea YouTube Comments on Sidewalk Autonomous Delivery Robots

Abstract

Sidewalk autonomous delivery robots (SADRs) are set to commence formal operations in South Korea, allowing the general public to encounter and interact with them in public spaces. Consequently, understanding the opinions of the populace regarding SADRs has become imperative, and one viable approach is the analysis of user-generated online comments. This research involved the analysis of 6,598 comments from nine YouTube videos to uncover the perspectives of South Korean YouTube users on SADRs. The text mining was executed through word frequency analysis and LDA topic modeling. Word frequency analysis revealed that, beyond search terms like "delivery" and "robot," the most frequently occurring words included "human," "fee," "delivery rider," "good," "sidewalk," and "use." The LDA topic modeling categorizes the identified themes into three: (1) SADRs replacing traditional manual delivery; (2) SADRs' operational technology; and (3) the real-world challenges and prospects of SADRs. This study has captured the sentiments of South Korean YouTube commenters towards SADRs, encompassing their positive feedback, concerns, and insights. It provides valuable direction for companies engaged in robotic innovation. Furthermore, it underscores the significance of leveraging YouTube video comments as a textual database in the field of robotics.