데이터 마이닝 분석을 통한 한국형 디스커버리 제도 도입에 관한 연구

초록

Civil litigation involving technology leakage faces structural challenges, particularly in proving infringement and calculating damages. Although the current legal framework includes a limited mechanism for requesting the submission of evidence, its scope is narrow, and it imposes a substantial burden of proof on the applicant, rendering it ineffective as a practical tool for evidence collection. Consequently, victims often abandon civil remedies and instead rely on criminal proceedings, leading to a distorted pattern of legal response. To establish the societal need for introducing a discovery system in Korea, a data-driven analysis is essential. This study collected and analyzed 1,554 domestic news articles published between January 2020 and May 2025 that discuss the discovery system. Both keyword frequency analysis based on text mining and BERTopic-based topic modeling were employed. The keyword analysis identified key terms such as “corporation,” “Korea,” “system,” “litigation,” “lawyer,” “United States,” “discovery,” and “introduction,” reflecting the discourse surrounding the adoption of the system. BERTopic analysis revealed eight major topics, primarily related to the discovery system, technology leakage, and industrial technology disputes among large enterprises. This research advances beyond traditional conceptual discussions by empirically demonstrating the social demand and policy legitimacy for introducing a discovery system in Korea through data mining of media discourse. Based on these findings, the study provides empirical grounds for evaluating the feasibility of a Korean-style discovery system and is expected to contribute as foundational material for future institutional reform discussions.

키워드