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http://dx.doi.org/10.14400/JDC.2020.18.9.181

Analyzing the Trend of Wearable Keywords using Text-mining Methodology  

Kim, Min-Jeong (Dept. of Consumer Economics, Sookmyung Women's University)
Publication Information
Journal of Digital Convergence / v.18, no.9, 2020 , pp. 181-190 More about this Journal
Abstract
The purpose of this study is to analyze the trends of wearable keywords using text mining methodology. To this end, 11,952 newspaper articles were collected from 1992 to 2019, and frequency analysis and bi-gram analysis were applied. The frequency analysis showed that Samsung Electronics, LG Electronics, and Apple were extracted as the highest frequency words, and smart watches and smart bands continued to emerge as higher frequency in terms of devices. As a result of the analysis of the bi-gram, it was confirmed that the sequence of two adjacent words such as world-first and world-largest appeared continuously, and related new bi-gram words were derived whenever issues or events occurred. This trend of wearable keywords will be useful for understanding the wearable trend and future direction.
Keywords
Wearable; News articles; Text Mining; Frequency Analysis; Bi-gram Analysis;
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