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@article{196829,
        author = {M. Malaiselvam and M. Naga Sundar and Mr. T. Maria Mahajan},
        title = {CAPTURING THE SENTIMENTS OF HYBRID CONFERENCES USING EMOJI- BASED QUESTIONNARIE AND AI EMOTION RECOGNITION},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {3505-3510},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196829},
        abstract = {Hybrid conferences and seminars have become increasingly popular due to their flexibility and accessibility. However, understanding participant engagement and emotional response in such environments remains a significant challenge. Traditional feedback systems are delayed and often ineffective. This paper proposes an intelligent sentiment analysis system that integrates facial emotion recognition with an emoji-based questionnaire to capture real-time audience feedback. The system utilizes computer vision techniques with OpenCV and Haar-Cascade classifiers for face detection, along with a Convolutional Neural Network (EmotionNet) for emotion classification. Additionally, an emoji-based feedback mechanism enables participants to express their sentiments quickly and intuitively. The combined approach enhances real-time interaction, improves audience engagement, and provides actionable insights for organizers. The proposed system demonstrates improved feedback accuracy, usability, and effectiveness in hybrid event environments.},
        keywords = {Sentiment Analysis, Hybrid Conferences, Emotion Recognition, OpenCV, CNN, Emoji Feedback},
        month = {April},
        }