텍스트 연결망 분석을 통한 감사청구 동향 분석

The demand for audit petitions from the public is increasing day by day, highlighting the significant role of the Board of Audit and Inspection. This study aims to analyze public demand related to audit petitions through newspaper articles addressing grievances and audit petitions. The articles analyzed are from the year 2023, using text mining techniques that employ context analysis to extract detailed contexts and derive keywords for network analysis. This helps to identify public preferences reflected in audit petitions and trends in how the media views these petitions. Furthermore, it aims to provide insights for departments and agencies conducting audit tasks on how to appropriately plan future audits based on the keywords and contexts embodying public demand. The results show that firstly, the public expects audit petitions to enhance the transparency of administration by ensuring fairness in project handling and clarifying suspicions. Secondly, environmental groups' audit petitions scored lower than expected in centrality indices, indicating low media and public interest in environmental audit petitions. Thirdly, keywords related to systems and processes had almost no influence in the network, confirming a lack of public and media interest in systemic improvements or procedural issues. These findings provide crucial information for assessing public interest and institutional responses to various topics.