Keyword Network Analysis on Free Semester Policy with Korean Newspaper Articles

Abstract

This study aims to explore issues emerged from Koreas Free Semester Policy through keyword network analysis on newspaper articles. Using web-scraping with Python, the published articles from 11 major daily newspapers between 2013 and 2017 were collected. After preprocessing the collected data, keyword frequency analysis and keyword network analysis were conducted in each of the five phases of the policy process in order to identify the keywords and to ascertain their association. Throughout all phases of the policy, promoting opportunities for career exploration and improving instruction methods via national and local support and cooperation were at the core of the policy. The analysis showed that there were visible changes as the policy progressed from one phase to another. Having identified the core issues surrounding Free Semester Policy, this research will be a stepping stone to analyze other education policies.