Exploring the Social Value of Care Robots: Text Mining and Semantic Network Analysis

Area of Science:

• Robotics
• Social Science
• Human-Computer Interaction

Background:

• The increasing demand for care services necessitates innovative solutions.
• Care robots are emerging technologies with the potential to address care gaps.

Purpose of the Study:

• To explore public discourse on care robots.
• To identify the social values associated with care robots.

Main Methods:

• Text mining and keyword extraction from Korean social media and portal sites (2021-2023).
• Topic modeling and semantic network analysis (UCINET 6.0) to analyze keyword associations.
• Thematic integration framework to synthesize findings and derive social value domains.

Main Results:

• Extracted 9,724 keywords from 21,216 documents; central keywords included 'older adult,' 'companion robot,' 'business,' 'service,' and 'artificial intelligence.'
• Identified four key topics: bridging care gaps, economic trends, multi-sector support, and government-led expansion.
• Semantic network analysis revealed eight clusters, integrated to define social values in health, labor, economy, and innovation.

Conclusions:

• Care robots possess potential beyond functional support, addressing social challenges and fostering care innovation.
• Current public discourse is provider-centric, lacking sufficient public engagement.
• Improved communication of social value and user-centered design are essential for effective implementation in care.