Purpose: This research was to understand people's perceptions and trends in wearable robots and the research questions were as follows: (1) investigating key terms related to wearable robots that were frequently used by and exposed to people and (2) analyzing relationships among those key terms. Design/methodology/approach: Textom, a big data collection and analysis software system, was used to collect data using the keyword – wearable robot. Findings: The frequency-inverse document frequency, term frequency and central analyses were investigated, and the major key terms related to wearable robots and their connectivity were identified. After performing network analysis and convergence of iterated correlations analyses using UCINET and NetDraw programs, the major key term categories were identified. Originality/value: It is important to understand how people think and perceive about wearable robots before developing wearable robots. The results of the research are expected to be helpful to better understand how people perceive and what key terms are mainly discussed by people in both countries and ultimately help when developing wearable robots with better market targeting approach methods.
|Number of pages||14|
|Journal||International Journal of Clothing Science and Technology|
|Publication status||Published - 2022 Mar 11|
Bibliographical noteFunding Information:
This work was supported by the Korean Government-Ministry of Trade, Industry and Energy (No. 20008912, S202005S00045).
© 2021, Emerald Publishing Limited.
All Science Journal Classification (ASJC) codes
- Business, Management and Accounting (miscellaneous)
- Materials Science (miscellaneous)
- Business, Management and Accounting(all)
- Polymers and Plastics