A research-oriented platform for controlled experimentation with Large Language Models
EmotionalChat is a full-stack web application designed as research infrastructure for conducting controlled experiments with Large Language Models in academic environments.
The platform addresses a critical need in AI research: providing educators and researchers with a flexible, ethically-designed tool for systematic investigation of conversational AI behavior, human-machine interaction patterns, and the effectiveness of advanced AI techniques like Retrieval-Augmented Generation (RAG).
Built with modern web technologies and cloud-native architecture, EmotionalChat enables researchers to create configurable conversational AI experiments, collect comprehensive data, and collaborate with teams—all while maintaining ethical research standards and participant privacy.
EmotionalChat serves as a research platform for academic experimentation with Large Language Models, enabling systematic study of:
Conduct controlled experiments, collect data, analyze AI behavior patterns, and publish findings in peer-reviewed journals.
Create educational experiences, design AI literacy curricula, and teach students about LLMs through hands-on experimentation.
Explore AI capabilities, understand model limitations, develop critical thinking about AI systems, and conduct thesis research.
Explore the comprehensive technical architecture, features, and implementation details below. Click any section to expand and see the full depth of the platform.
EmotionalChat demonstrates the intersection of software engineering excellence and academic research needs. The platform provides a robust, scalable, and ethically-designed foundation for advancing our understanding of Large Language Models and their impact on human communication.