9th International Conference on ICT for Sustainable Development

Authors - Rushabh Dabhade, Gaurav Dhokane, Aryan Mahajan, Rishikesh Sutar
Abstract - In this study, a novel machine learning method for real-time sentiment analysis in WhatsApp con- versations is presented. We carefully process the text input, extracting pertinent elements by utilising cutting-edge natural language processing tools. The approach ensures precise sentiment classification by fusing state-of-the-art deep learning models with conventional machine learning techniques in a seam- less manner. Creating a sentiment vocabulary specifically for WhatsApp and adapted to the different language nuances present in these chat discussions is one of the study’s unique features. Moreover, our investigation goes farther to comprehend the subtle impact of temporal dynamics on sentiment patterns, offering important perspectives on the dynamic emotional terrain of this communication medium. Proven adaptability and appropriateness are demonstrated by the suggested framework’s exceptional accuracy across a variety of datasets.Our methodology has potential uses in social media analytics and mental health monitoring, in addition to the immediate context of sentiment analysis. This Research plays a significant role in the continued development of sentiment analysis techniques, especially in the dynamic context of modern communication platforms.