Analysis of Behavior in Chat Applications using Natural Language Processing

The ubiquitous use of digital messaging platforms, such as WhatsApp, has revolutionized human communication. Our research 'Be-chat delves into the realm of Natural Language Processing (NLP) to conduct anin- depth analysis of user behaviour within chat conversations. The study encompasses sentiment analysis, flirtation detection, and time-based behaviour analysis, providing valuable insights for parental oversight, law enforcement investigations, and fostering a safer onlineenvironment. In today's digital age, conversations predominantly occur through messaging platforms. The process to identify nuanced emotions, navigating a variety of languages and situations, and guaranteeing real-time monitoring when utilizing NLP for behavior analysis is more challenging job. Be-chatdelves into the analysis of people's behaviour through Natural Language Processing (NLP) to encompass various chat applications. The study primarily aims to develop an NLP-based solution for monitoring and filtering inappropriate messages in real-time. In addition, it exploresthe applications of sentiment analysis and time analysis for various use cases, including parental oversight and lawenforcement investigations