텍스트 네트워크 분석을 활용한 공공부문의 사회적경제 관련 이슈 도출 : 신용보증기금의 사례를 중심으로

This study is to drew policy issues from the Korea Credit Guarantee Fund, a major policy organization for social economy policy promotion, through analysis of big data-based text networks, considering the situation in which public institutions are in full swing promoting social economic policies as the government's policy measures on social economy and finance were announced. As a result of the analysis, the words selected as the top keyword in frequency analysis and degree centrality in relation to the social economy promotion of the Korea Credit Guarantee Fund were, support / social economy / enterprises / shinbo / small and medium enterprises / financial support / society / Daegu / making a contract / agreement / job / business agreement etc. Based on the results of the analysis, it is necessary to develop and apply a performance evaluation model to evaluate and measure the performance of public institutions' social economy support, to analyze and evaluate the government's social economy activation policy from a big data perspective, to encourage and foster the efforts of public institutions to strengthen their own capacity, to utilize the social economy as a powerful policy tool for job creation, and actively to seek to create organic relevance and synergies between policy tasks were suggested as policy implications.