Abstract :

This Literature Review Explores The Current State Of Research On Real-time Chat Applications That Have Integrated Emotion Detection Capabilities. We Analyze The Studies Published Between 2018 And 2024, Concentrating On Three Aspects: (1) Innovations In Real-time Chat Technology, With A Focus On MERN Stack-based Developments; (2) Methods Of Emotion Detection In Textbased Communication; And (3) Emotion Detection Integration Within Chat Interfaces. Our Survey Indicates Huge Strides In Deep Learning Models For The Detection Of Emotion. Recent Approaches Have Been Able To Show Up To 91.5% Accuracy. Along The Journey, We Identify Some Challenging Areas Such As Real-time Implementation Issues, Privacy Issues, And User Experience Design. We Conclude With Future Directions Of Research In This Field: Multimodal Emotion Detection, Cross-lingual Support, And Ethical Considerations In Emotion-aware Chat Systems. Keywords—Real-time Emotion Detection, Chat Applications, MERN Stack, NLP, Deep Learning, AI.

Published:

25-9-2025

Issue:

Vol. 25 No. 9 (2025)

Page Nos:

205-212

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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