Sentiment Analysis of Online Public Opinion on University Faculty Misconduct: Evidence from Six Typical Cases on Weibo

This study combines LDA-based topic analysis and TextMind-based sentiment analysis to examine online public opinion on faculty misconduct in Chinese higher education, based on Weibo comments from six representative cases classified into Academic Misconduct Cases and Improper Personal Conduct Cases. The results show three main patterns. First, public discussion centered on accountability, student protection, university responses, and handling procedures. Second, different types of misconduct triggered different concerns: Academic Misconduct Cases were more closely related to research integrity, supervisor responsibility, and students’ academic rights, whereas Improper Personal Conduct Cases more often involved teacher–student boundaries, harassment allegations, abuse of power, and fairness disputes. Third, sentiment distributions differed significantly across cases and showed topic-level variation. Positive sentiment did not indicate approval of faculty misconduct, but mainly reflected support for whistleblowers, affected students, accountability measures, and student protection; negative sentiment was more salient in themes related to academic fraud, insufficient sanctions, opaque investigations, and procedural questioning. These findings show that faculty misconduct cases can shift from individual ethical controversies to public evaluations of institutional responsibility and procedural credibility, suggesting that universities should strengthen data-driven public opinion monitoring, improve procedural transparency, protect students’ rights, and move from reactive crisis response toward earlier intervention and more proactive governance.