The purpose of this study is to present basic data for the recognition of the life planning in the Big Data and the derivation of new value. To do this, researchers used the social matrix program textom to collect and analyze data. The subjects of the analysis were Naver, Daum, which are easy to access information, and web, blog, news, cafe and intellectual provided by Google. In order to see the frequency of use of words related to youth + life planning and the network between words, we analyzed network analysis, visualization, and CONCOR analysis using the NetDraw function of Ucinet6 program to understand the relationship between blocks. The collected data were refined and 73 keywords were selected based on the word frequency. The selected key words were converted into matrix data, and the main word frequency analysis, semantic network analysis, and centrality analysis were performed. The data analysis period was limited to three years from April 1, 2015 to March 31, 2018. As a result, it was found that the life planning for the adolescents perceived through the Big Data had a lot of relevance to support , education , youth , program . In the centrality analysis, interaction , program and education appeared in the center of the meaning network analysis. In the centrality analysis, the keyword with the highest interaction was start and the keyword with the highest centrality in. The keyword with the highest mediation centrality was interest . Meaningful words for the life planning of adolescents were words about education, program, and career.