This study analyzes the characteristics of parent-related topics recognized by society by analyzing articles related to parents through text mining and semantic network analysis. The newspaper articles analyzed were collected using the newspaper article search service (www.bigkinds.or.kr) provided by Korea Press Foundation. The collection period is January 1, 1997. From 2017 to February 28, 2013, a total of 113,472 articles were extracted, including 103,897 parents, 943 school attendance, 4,526 parent education, 113 father education, 3,020 parent education, and 973 parent consultation. According to the results of the analysis, first, the social issues and interests related to the parents are continuously increasing. Second, parents, students, and schools have strong connections with each other. On the other hand, teachers, one of the three subjects of education, have relatively low connectivity in parent-related articles. Third, middle school has lower TF-IDF (Term Frequency-Inverse Document Frequency) than elementary school high school, which proves the social characteristics that the relative interest in middle school is low. Convergence of iterated CORrelations (CONCOR) analysis, which repeatedly performed a correlation analysis to find an appropriate level of similarity groups, clearly distinguished groups. This study analyzes the text mining of newspaper articles related to parents. Although there is a first attempt in the field of parents' involvement, there is a limit to an in-depth analysis of the social phenomena associated with parents. To complement this, it is also necessary to analyze articles related to parents from the perspective of opinion mining.