Advancing Mobile App Feedback: Structured Review Systems and NLP Integration
This research project focuses on enhancing mobile app review systems on platforms like the Apple App Store and Google Play. The project addresses current issues with review categorisation and authenticity by integrating Socio-Technical Grounded Theory (STGT) and Natural Language Processing (NLP), specifically using advanced tools like GPT-4, to analyse user reviews more effectively. This approach aims to provide deeper insights into app functionalities and user satisfaction.
A key innovation is the development of an interactive UI prototype for submitting reviews. This prototype introduces structured categorisation and a "verified download" tag to ensure review authenticity. This new system is designed to help developers prioritise improvements based on genuine user feedback and enable users to make more informed decisions about apps.
The project's main contributions are the development of a structured and authentic review system, an interactive UI prototype, and a tool that enhances the review submission and analysis process. Future work includes further integrating STGT with NLP techniques to improve the accuracy of sentiment and entity recognition in user feedback. The ultimate goal is to improve the quality and reliability of user feedback in the mobile app ecosystem.
Project Lead
Dr Omar Haggag
Project team
Prof John Grundy, Prof Rashina Hoda
