Exploring Perceptions of Service Robotics Through Semantic Network Analysis

This study utilizes Textom to systematically analyze public perceptions of service robots, based on data from social media, online news, and portal sites, and to explore the relationships between related keywords. The keyword frequency analysis revealed the following key terms in descending order: ‘technology,’ ‘serving,’ ‘industry,’ ‘corporation,’ ‘business,’ ‘development,’ ‘provision,’ ‘autonomous driving,’ and ‘market.’ CONCOR analysis identified four clusters: ‘Service Robotics Industry and Market,’ ‘Service Operations and Customer Touchpoints,’ ‘Specialized Application Fields,’ amd ‘Smart Technologies and Platforms.’ In conclusion, this study offers concrete policy recommendations aimed at enhancing the social acceptance of service robots and strengthening their future roles to deliver practical value to users.