Big data analyses on key terms of wearable robots in social network services

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)285-298
Number of pages14
JournalInternational Journal of Clothing Science and Technology
Issue number2
Publication statusPublished - 2022 Mar 11

Bibliographical note

Publisher Copyright:
© 2021, Emerald Publishing Limited.

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting (miscellaneous)
  • Materials Science (miscellaneous)
  • General Business,Management and Accounting
  • Polymers and Plastics


Dive into the research topics of 'Big data analyses on key terms of wearable robots in social network services'. Together they form a unique fingerprint.

Cite this