Mining user feedback on dictionary apps: A sentiment analysis of the Longman Dictionary of Contemporary English (LDOCE) app

With the growing integration of mobile technology into language learning, dictionary apps have become useful tools for English as a Foreign Language (EFL) learners. This study investigated Chinese user feedback on the Longman Dictionary of Contemporary English (LDOCE) app to uncover user needs, perceptions, and sentiments. Based on 4,643 user comments collected between August 2016 and December 2024, the research employed word frequency analysis, semantic network construction, Latent Dirichlet Allocation (LDA) topic modelling, and sentiment analysis. Five key themes were identified: technical issues, version updates, lexical content, dictionary perceptions, and pronunciation. The findings showed that while users valued the app’s authoritative content and learning features, they also raised concerns about app crashes, monetization, and insufficient pronunciation options. Furthermore, although the app’s functions have evolved rapidly over the past decade, the dictionary content itself has only been updated once, raising questions about content maintenance in dictionary apps. This study demonstrates that user feedback provides valuable insights that can guide both the functional design and lexicographic priorities of future dictionary apps.