An Analysis of Consumers’ Opinion on Fashion Influencer using Big Data

Han, Ki Hyang

doi:10.9728/dcs.2019.20.11.2283

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…Similar to Kim and Lee's (2019) research, Cho (2020) also used Textom to determine the word frequency, frequency-inverse document frequency (TF-IDF) and connection center. In the study by Han (2019), the important words related to fashion influencer for two years were collected using the Textom, UCINET and NetDraw programs and the network analyses and CONCOR analyses were conducted. This study found the words with the highest frequency and identified influencing factors to consumers (Han, 2019).…”

Section: Theoretical Backgroundsmentioning

confidence: 99%

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

Han

Koo

2021

IJCST

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PurposeThis 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/approachTextom, a big data collection and analysis software system, was used to collect data using the keyword – wearable robot.FindingsThe 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/valueIt 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.

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Section: Theoretical Backgroundsmentioning

confidence: 99%

“…In the study by Han (2019), the important words related to fashion influencer for two years were collected using the Textom, UCINET and NetDraw programs and the network analyses and CONCOR analyses were conducted. This study found the words with the highest frequency and identified influencing factors to consumers (Han, 2019).…”

Section: Theoretical Backgroundsmentioning

confidence: 99%