Automated Citation Analysis and Visualization for Supreme Court Judgements

This paper proposes an innovative method for facilitating access to Supreme Court decisions through citation analysis. Leveraging natural language processing tools like the Gensim and NLTK libraries, our approach retrieves relevant documents and paragraphs from two distinct datasets: one representing current judgments and the other serving as a reference corpus. Through comprehensive testing and evaluation, we validate the reliability and efficacy of our methodology in extracting pertinent judgments. Our findings underscore how this system can streamline legal research, providing users with valuable insights and credible sources to bolster their analyses and arguments. Additionally, we discuss future research avenues and potential applications, underscoring the significance of citation analysis in legal information retrieval systems.