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

초록

Purpose: This study aimed to explore the public discourse surrounding care robots and identify their potential social values. Methods: Data related to care robots were collected from major Korean portal sites and social media between January 1, 2021, and December 31, 2023, using TEXTOM. Core keywords were extracted through text mining. Topic modeling and semantic network analysis using UCINET 6.0 were conducted to examine keyword associations and network structure. An analytic framework based on thematic integration was applied to synthesize the findings and derive social value domains. Results: A total of 9724 keywords were extracted from 21,216 documents. High-frequency and central keywords included older adult, companion robot, business, service, and artificial intelligence. Topic modeling identified four major topics: (1) companion robots supporting care to bridge the care gap, (2) care robots leading new economic trends, (3) care robots supporting human care across various sectors, and (4) government-led expansion of social care through care robots. Eight clusters were identified through semantic network analysis. By applying the analytic framework, these clusters were systematically integrated with topic modeling results, and the social values associated with care robots were categorized into four domains: health, labor, economy, and innovation. Conclusion: Care robots have the potential to go beyond functional support by addressing broader social challenges and contributing to care innovation. However, current discourse remains provider driven with limited public engagement. There is a need to enhance communication of care robots’ social value and promote user-centered approaches in nursing and care practice.

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