Research Trends Related on Hair Style in the Text Mining of Big Data Analysis

This study identified research trends by conducting keyword word frequency (TF), related word analysis (N-gram), and reverse document frequency (TF-IDF) through text mining, which analyzes text, which is unstructured data in big data, using the title and Korean abstract of domestic academic papers searched as hairstyles keywords in the Research Information Service (RISS). Through the research results, it was confirmed that hairstyles represent the characteristics of the times, and they are producing them or writing papers to understand preferences through statistics. The purpose of this study is to provide basic data to identify research trends through keywords extracted through text mining that analyzes text, which is unstructured data, in a new way with the development of big data processing technology.