User Perception and Sentiment Analysis of Knee exoskeletons for Hiking Based on Social Media Comments: A Preliminary Study

Abstract

With the rapid development of wearable robotic technologies, knee exoskeletons especially for hiking have emerged as assistive devices intended to reduce physical fatigue during outdoor activities. As these systems gradually enter early-stage consumer markets, understanding users’ real-world perceptions is important for human-centered design and evaluation. This study investigates public perceptions of knee exoskeletons through analysis of user-generated comments from social media. Approximately 9,000 comments related to knee exoskeletons were collected from the Chinese social media platform Rednote over a six-month period. After data cleaning and preprocessing, 7,280 valid comments were retained. Chinese word segmentation and Term Frequency–Inverse Document Frequency weighting were applied to extract textual features, and K-means clustering was used to identify major thematic categories in user discussions. In addition, lexicon-based sentiment analysis using the National Taiwan University Sentiment Dictionary was conducted to examine emotional tendencies. The results indicate that user discussions mainly focus on product attributes and usage scenarios. Neutral expressions (4755) dominate the comments, while negative sentiment (1304) slightly outweighs positive sentiment (1221) among emotionally polarized comments, reflecting a cautious and pragmatic public attitude. Although users recognize the potential benefits of physical assistance, concerns regarding comfort, weight, usability, and practical value remain prominent. Overall, this study demonstrates the feasibility of social media comment analysis as a complementary approach for evaluating human factors in emerging wearable robotic systems.

Keywords: Exoskeletons, Wearable Robotic, User Perception, Sentiment Analysis

DOI: 10.54941/ahfe1007679