HeritEdge: Diversity-Aware Interactive Framework for Feedback Sentiment Classification and Trend Monitoring

Sayali Deshmukh1, Shreya Deshmukh2, Darshani Dhotre3 , Shrawani Disale4

Zeal College of Engineering and Research Pune (Computer Engineering)1,2,3,4

Abstract— Public events generate a continuous stream of participant feedback that often remains underutilized due to delays in analysis and interpretation. This paper introduces HeritEdge, a diversity-aware and interactive framework developed to analyze event feedback in real time and transform it into meaningful operational insights. The proposed system combines Firebase Firestore, Cloud Functions, Flutter, and machine-learning techniques to process user responses as they are submitted. Beyond identifying sentiment polarity, the framework performs contextual categorization of feedback, enabling organizers to detect concerns related to crowd movement, food services, transportation, safety, and event infrastructure. Unlike conventional feedback-management solutions that rely on retrospective analysis, HeritEdge supports continuous monitoring and dynamic trend discovery throughout the event lifecycle. By integrating cloud-native technologies with intelligent sentiment analytics, the framework enables faster response mechanisms, evidence-based decision making, and improved participant engagement. Experimental observations demonstrate that the proposed architecture provides a scalable and practical approach for modern event-management environments where timely insight generation is essential.

Keywords— Sentiment Analysis, Firebase Firestore, Flutter, Machine Learning, Event Analytics, Real-Time Feedback Processing, Trend Monitoring, Smart Event Management, Cloud Computing.