People’s Behaviour Analysis in Chat Message using Natural Language Processing

Nowadays, the mode of communication is mainly through messages. A lot of information has been conveyed through WhatsApp. WhatsApp is the most popular chat application with active users of more than 650 million. It has been widely used by all, especially among the business people and youngsters. Using several analyzing tools, users can analyse the WhatsApp group chat or personal chat. Authentically users wish to analyse their chat for several purposes. This research work is intended to perform a flirt analysis and time analysis. This project has many use cases like the parent, who wants to analyze their child chat; the police, who want to get valuable information from culprit chat; the business people, who wants to know the status of the business in the group chat. Using the Deep Learning model (NLP), sentimental analysis has been performed for each text. This helps to find the state of mind of the chatters. Further, this research work calculates the number of positive and negative statements that are used by each person in the text by using the text mining concept. As now due to this pandemic situation, every conversation and also the important discussion has been done through the WhatsApp and it was highly needed for the person who wants to check their child’s conversation and also for the higher authority for enquiry and for the business chair person who are needed to analyse their business well being group can also be used for their personal usage of analyse using the algorithm in this method.