This study by Menghui Li and Zhesi Shen examines the prevalence and severity of academic misconduct across various disciplines and topics. Using data from 25,710 cases of academic misconduct retraction (AMR) out of 31,003 retracted articles between 2000 and 2023, the authors categorized the retracted articles into 10 macro-topics and 326 meso-topics. The findings reveal that the rate of AMR varies widely, with some disciplines experiencing significantly higher rates than others. For instance, the Electrical Engineering, Electronics, and Computer Science (EE & Comp Sci) discipline has an AMR rate of up to 17.4%, while the Physics discipline has a much lower rate of 1.7%. The Clinical and Life Sciences (Clin & Life Sci) discipline has the highest number of AMRs at 12.565, with an AMR rate of 8.9%. The study also highlights that at least one instance of academic misconduct exists in 324 out of 326 meso-topics. A science map, generated using VOSviewer, effectively visualizes the citation network among these topics, showing that the severity of misconduct varies significantly. For example, the Micro and Long Noncoding RNA (mLncRNA) topic in the Telecommunications discipline has the highest number of AMRs (2,105) and the highest AMR index (20.8). In contrast, topics in Mathematics, Physics, and Chemistry have lower AMR indices, indicating less severe misconduct. The study further analyzes the reasons for misconduct, finding that while traditional forms such as fabrication, falsification, and plagiarism remain common, new forms like Fake Peer-review, Paper Mill, and artificial intelligence-generated content (AIGC) have become more prevalent. The AMR index, defined as the ratio of AMR to published articles, helps assess the severity of misconduct in specific entities. The results emphasize the need for discipline-specific interventions to address the varying degrees of academic misconduct across different topics.This study by Menghui Li and Zhesi Shen examines the prevalence and severity of academic misconduct across various disciplines and topics. Using data from 25,710 cases of academic misconduct retraction (AMR) out of 31,003 retracted articles between 2000 and 2023, the authors categorized the retracted articles into 10 macro-topics and 326 meso-topics. The findings reveal that the rate of AMR varies widely, with some disciplines experiencing significantly higher rates than others. For instance, the Electrical Engineering, Electronics, and Computer Science (EE & Comp Sci) discipline has an AMR rate of up to 17.4%, while the Physics discipline has a much lower rate of 1.7%. The Clinical and Life Sciences (Clin & Life Sci) discipline has the highest number of AMRs at 12.565, with an AMR rate of 8.9%. The study also highlights that at least one instance of academic misconduct exists in 324 out of 326 meso-topics. A science map, generated using VOSviewer, effectively visualizes the citation network among these topics, showing that the severity of misconduct varies significantly. For example, the Micro and Long Noncoding RNA (mLncRNA) topic in the Telecommunications discipline has the highest number of AMRs (2,105) and the highest AMR index (20.8). In contrast, topics in Mathematics, Physics, and Chemistry have lower AMR indices, indicating less severe misconduct. The study further analyzes the reasons for misconduct, finding that while traditional forms such as fabrication, falsification, and plagiarism remain common, new forms like Fake Peer-review, Paper Mill, and artificial intelligence-generated content (AIGC) have become more prevalent. The AMR index, defined as the ratio of AMR to published articles, helps assess the severity of misconduct in specific entities. The results emphasize the need for discipline-specific interventions to address the varying degrees of academic misconduct across different topics.